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1. Novel CNC/silica hybrid as potential reinforcing filler for natural rubber compounds

Author: Ali, S, Imiete, I, Orlandi, M, Castellani, L, Hanel, T, Zoia, L, Ali, SD, IMIETE, IIKPOEMUGH ELO, Orlandi, ME, Ali, S, Imiete, I, Orlandi, M, Castellani, L, Hanel, T, Zoia, L, Ali, SD, IMIETE, IIKPOEMUGH ELO, and Orlandi, ME
Abstract: This work describes the development of a low-density, renewable, and high reinforcing filler for natural rubber (NR) compounds. The cellulose nanocrystal (CNC)-based hybrid filler was synthesized by decorating the surface of CNCs with silica using a simple and efficient coprecipitation method. The properties of the prepared hybrid were investigated by field emission scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, nitrogen physisorption measurements, and Thermogravimetric analysis. Then, the prepared hybrid was incorporated in NR using two different approaches, namely, dry mixing and coprecipitation. The dynamic and tensile mechanical properties of the hybrid/NR compounds were evaluated indicating that: the coprecipitation method was found much more effective for homogeneous dispersion and the CNC/silica hybrid provided quite higher reinforcement to NR than reference silica; however, much lower density of the final compounds was obtained.
Published: 2020

2. Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: A systematic analysis from the Global Burden of Disease Study 2016

Author: Fullman, N, Yearwood, J, Abay, SM, Abbafati, C, Abd-Allah, F, Abdela, J, Abdelalim, A, Abebe, Z, Abebo, TA, Aboyans, V, Abraha, HN, Abreu, DMX, Abu-Raddad, LJ, Adane, AA, Adedoyin, RA, Adetokunboh, O, Adhikari, TB, Afarideh, M, Afshin, A, Agarwal, G, Agius, D, Agrawal, A, Agrawal, S, Ahmad Kiadaliri, A, Aichour, MTE, Akibu, M, Akinyemi, RO, Akinyemiju, TF, Akseer, N, Al Lami, FH, Alahdab, F, Al-Aly, Z, Alam, K, Alam, T, Alasfoor, D, Albittar, MI, Alene, KA, Al-Eyadhy, A, Ali, SD, Alijanzadeh, M, Aljunid, SM, Alkerwi, A, Alla, F, Allebeck, P, Allen, C, Alomari, MA, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Alvis-Guzman, N, Amare, AT, Amenu, K, Ammar, W, Amoako, YA, Anber, N, Andrei, CL, Androudi, S, Antonio, CAT, Araújo, VEM, Aremu, O, Ärnlöv, J, Artaman, A, Aryal, KK, Asayesh, H, Asfaw, ET, Asgedom, SW, Asghar, RJ, Ashebir, MM, Asseffa, NA, Atey, TM, Atre, SR, Atteraya, MS, Avila-Burgos, L, Avokpaho, EFGA, Awasthi, A, Ayala Quintanilla, BP, Ayalew, AA, Ayele, HT, Ayer, R, Ayuk, TB, Azzopardi, P, Azzopardi-Muscat, N, Babalola, TK, Badali, H, Badawi, A, Banach, M, Banerjee, A, Banstola, A, Barber, RM, Barboza, MA, Barker-Collo, SL, Bärnighausen, T, Barquera, S, Barrero, LH, Bassat, Q, Basu, S, Baune, BT, Bazargan-Hejazi, S, Bedi, N, and Beghi, E
Subjects: General & Internal Medicine, Humans, Wounds and Injuries, Noncommunicable Diseases, Communicable Diseases, Health Services Accessibility, Quality of Health Care, Global Burden of Disease
Abstract: Copyright © 2018 The Author(s). Published by Elsevier Ltd. Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8-98·1) in Iceland, followed by 96·6 (94·9-97·9) in Norway and 96·1 (94·5-97·3) in the Netherlands, to values as low as 18·6 (13·1-24·4) in the Central African Republic, 19·0 (14·3-23·7) in Somalia, and 23·4 (20·2-26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1-93·6) in Beijing to 48·0 (43·4-53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6-68·8) in Goa to 34·0 (30·3-38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle- SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view - and subsequent provision - of quality health care for all populations.
Published: 2018

3. Alcohol use and burden for 195 countries and territories, 1990-2016: A systematic analysis for the Global Burden of Disease Study 2016

Author: Griswold, MG, Fullman, N, Hawley, C, Arian, N, Zimsen, SRM, Tymeson, HD, Venkateswaran, V, Tapp, AD, Forouzanfar, MH, Salama, JS, Abate, KH, Abate, D, Abay, SM, Abbafati, C, Abdulkader, RS, Abebe, Z, Aboyans, V, Abrar, MM, Acharya, P, Adetokunboh, OO, Adhikari, TB, Adsuar, JC, Afarideh, M, Agardh, EE, Agarwal, G, Aghayan, SA, Agrawal, S, Ahmed, MB, Akibu, M, Akinyemiju, T, Akseer, N, Al Asfoor, DH, Al-Aly, Z, Alahdab, F, Alam, K, Albujeer, A, Alene, KA, Ali, R, Ali, SD, Alijanzadeh, M, Aljunid, SM, Alkerwi, A, Allebeck, P, Alvis-Guzman, N, Amare, AT, Aminde, LN, Ammar, W, Amoako, YA, Amul, GGH, Andrei, CL, Angus, C, Ansha, MG, Antonio, CAT, Aremu, O, Ärnlöv, J, Artaman, A, Aryal, KK, Assadi, R, Ausloos, M, Avila-Burgos, L, Avokpaho, EFGA, Awasthi, A, Ayele, HT, Ayer, R, Ayuk, TB, Azzopardi, PS, Badali, H, Badawi, A, Banach, M, Barker-Collo, SL, Barrero, LH, Basaleem, H, Baye, E, Bazargan-Hejazi, S, Bedi, N, Béjot, Y, Belachew, AB, Belay, SA, Bennett, DA, Bensenor, IM, Bernabe, E, Bernstein, RS, Beyene, AS, Beyranvand, T, Bhaumik, S, Bhutta, ZA, Biadgo, B, Bijani, A, Bililign, N, Birlik, SM, Birungi, C, Bizuneh, H, Bjerregaard, P, Bjørge, T, Borges, G, Bosetti, C, Boufous, S, Bragazzi, NL, Brenner, H, Butt, ZA, Griswold, MG, Fullman, N, Hawley, C, Arian, N, Zimsen, SRM, Tymeson, HD, Venkateswaran, V, Tapp, AD, Forouzanfar, MH, Salama, JS, Abate, KH, Abate, D, Abay, SM, Abbafati, C, Abdulkader, RS, Abebe, Z, Aboyans, V, Abrar, MM, Acharya, P, Adetokunboh, OO, Adhikari, TB, Adsuar, JC, Afarideh, M, Agardh, EE, Agarwal, G, Aghayan, SA, Agrawal, S, Ahmed, MB, Akibu, M, Akinyemiju, T, Akseer, N, Al Asfoor, DH, Al-Aly, Z, Alahdab, F, Alam, K, Albujeer, A, Alene, KA, Ali, R, Ali, SD, Alijanzadeh, M, Aljunid, SM, Alkerwi, A, Allebeck, P, Alvis-Guzman, N, Amare, AT, Aminde, LN, Ammar, W, Amoako, YA, Amul, GGH, Andrei, CL, Angus, C, Ansha, MG, Antonio, CAT, Aremu, O, Ärnlöv, J, Artaman, A, Aryal, KK, Assadi, R, Ausloos, M, Avila-Burgos, L, Avokpaho, EFGA, Awasthi, A, Ayele, HT, Ayer, R, Ayuk, TB, Azzopardi, PS, Badali, H, Badawi, A, Banach, M, Barker-Collo, SL, Barrero, LH, Basaleem, H, Baye, E, Bazargan-Hejazi, S, Bedi, N, Béjot, Y, Belachew, AB, Belay, SA, Bennett, DA, Bensenor, IM, Bernabe, E, Bernstein, RS, Beyene, AS, Beyranvand, T, Bhaumik, S, Bhutta, ZA, Biadgo, B, Bijani, A, Bililign, N, Birlik, SM, Birungi, C, Bizuneh, H, Bjerregaard, P, Bjørge, T, Borges, G, Bosetti, C, Boufous, S, Bragazzi, NL, Brenner, H, and Butt, ZA
Abstract: Background: Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted lifeyears (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods: Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health. Findings: Globally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2·2% (95% uncertainty interval [UI] 1·5-3·0) of age-standardised female deaths and 6·8% (5·8-8·0) of agestandardised male deaths. Among the population aged 15-49 years, alcohol use was the leading risk factor globally in 2016, with 3·8% (95% UI 3·2-4·3) of female deaths and 12·2% (10·8-13·6) of male deaths attributable to alcohol use. For the population aged 15-49 years, female attributable DALYs were 2·3% (95% UI 2·0-2·6) and male attributab
Published: 2018

4. Tyre for vehicle wheels comprising a composite reinforcing filler, masterbatch and coating a reinforcing filler

Author: Castellani, L, Zoia, L, Ali, SD, Orlandi, M, Hanel, T, Castellani, L, Zoia, L, Ali, S, Orlandi, M, and Hanel, T
Subjects: cellulose silica core shell filler natural rubber tire
Abstract: The vehicle wheels comprise a tire of ≥1 structural element comprising a vulcanized elastomeric material obtained by vulcanizing compn. comprising ≥1 vulcanizable diene elastomeric polymer and ≥1 composite reinforcing filler. A process for producing a tire comprises the composite reinforcing filler, a masterbatch comprising the composite reinforcing filler and a process for producing the composite reinforcing filler
Published: 2017

5. Software – defined networking based secure rout-ing in mobile ad hoc network

Author: Prasad, B. V. V. S., primary and Salman Ali, Sd., additional
Published: 2017
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6. Healthcare Access and Quality Index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990–2015: a novel analysis from the Global Burden of Disease Study 2015

Author: Barber, RM, Fullman, N, Sorensen, RJD, Bollyky, T, McKee, M, Nolte, E, Abajobir, AA, Abate, KH, Abbafati, C, Abbas, KM, Abd-Allah, F, Abdulle, AM, Abdurahman, AA, Abera, SF, Abraham, B, Abreha, GF, Adane, K, Adelekan, AL, Adetifa, IMO, Afshin, A, Agarwal, A, Agarwal, SK, Agarwal, S, Agrawal, A, Kiadaliri, AA, Ahmadi, A, Ahmed, KY, Ahmed, MB, Akinyemi, RO, Akinyemiju, TF, Akseer, N, Al-Aly, Z, Alam, K, Alam, N, Alam, SS, Alemu, ZA, Alene, KA, Alexander, L, Ali, R, Ali, SD, Alizadeh-Navaei, R, Alkerwi, A, Alla, F, Allebeck, P, Allen, C, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Martin, EA, Alvis-Guzman, N, Amare, AT, Amini, E, Ammar, W, Amo-Adjei, J, Amoako, YA, Anderson, BO, Androudi, S, Ansari, H, Ansha, MG, Antonio, CAT, Ärnlöv, J, Artaman, A, Asayesh, H, Assadi, R, Astatkie, A, Atey, TM, Atique, S, Atnafu, NT, Atre, SR, Avila-Burgos, L, Avokpaho, EFGA, Quintanilla, BPA, Awasthi, A, Ayele, NN, Azzopardi, P, Saleem, HOB, Bärnighausen, T, Bacha, U, Badawi, A, Banerjee, A, Barac, A, Barboza, MA, Barker-Collo, SL, Barrero, LH, Basu, S, Baune, BT, Baye, K, Bayou, YT, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Béjot, Y, Bello, AK, Bennett, DA, Bensenor, IM, Berhane, A, Bernabé, E, Bernal, OA, Beyene, AS, Beyene, TJ, Bhutta, ZA, Biadgilign, S, Bikbov, B, Birlik, SM, Birungi, C, Biryukov, S, Bisanzio, D, Bizuayehu, HM, Bose, D, Brainin, M, Brauer, M, Brazinova, A, Breitborde, NJK, Brenner, H, Butt, ZA, Cárdenas, R, Cahuana-Hurtado, L, Campos-Nonato, IR, Car, J, Carrero, JJ, Casey, D, Caso, V, Castañeda-Orjuela, CA, Rivas, JC, Catalá-López, F, Cecilio, P, Cercy, K, Charlson, FJ, Chen, AZ, Chew, A, Chibalabala, M, Chibueze, CE, Chisumpa, VH, Chitheer, AA, Chowdhury, R, Christensen, H, Christopher, DJ, Ciobanu, LG, Cirillo, M, Coggeshall, MS, Cooper, LT, Cortinovis, M, Crump, JA, Dalal, K, Danawi, H, Dandona, L, Dandona, R, Dargan, PI, das Neves, J, Davey, G, Davitoiu, DV, Davletov, K, De Leo, D, Del Gobbo, LC, del Pozo-Cruz, B, Dellavalle, RP, Deribe, K, Deribew, A, Des Jarlais, DC, Dey, S, Dharmaratne, SD, Dicker, D, Ding, EL, Dokova, K, Dorsey, ER, Doyle, KE, Dubey, M, Ehrenkranz, R, Ellingsen, CL, Elyazar, I, Enayati, A, Ermakov, SP, Eshrati, B, Esteghamati, A, Estep, K, Fürst, T, Faghmous, IDA, Fanuel, FBB, Faraon, EJA, Farid, TA, Farinha, CSES, Faro, A, Farvid, MS, Farzadfar, F, Feigin, VL, Feigl, AB, Fereshtehnejad, S-M, Fernandes, JG, Fernandes, JC, Feyissa, TR, Fischer, F, Fitzmaurice, C, Fleming, TD, Foigt, N, Foreman, KJ, Forouzanfar, MH, Franklin, RC, Frostad, J, G/hiwot, TT, Gakidou, E, Gambashidze, K, Gamkrelidze, A, Gao, W, Garcia-Basteiro, AL, Gebre, T, Gebremedhin, AT, Gebremichael, MW, Gebru, AA, Gelaye, AA, Geleijnse, JM, Genova-Maleras, R, Gibney, KB, Giref, AZ, Gishu, MD, Giussani, G, Godwin, WW, Gold, A, Goldberg, EM, Gona, PN, Goodridge, A, Gopalani, SV, Goto, A, Graetz, N, Greaves, F, Griswold, M, Guban, PI, Gugnani, HC, Gupta, PC, Gupta, R, Gupta, T, Gupta, V, Habtewold, TD, Hafezi-Nejad, N, Haile, D, Hailu, AD, Hailu, GB, Hakuzimana, A, Hamadeh, RR, Hambisa, MT, Hamidi, S, Hammami, M, Hankey, GJ, Hao, Y, Harb, HL, Hareri, HA, Haro, JM, Hassanvand, MS, Havmoeller, R, Hay, RJ, Hay, SI, Hendrie, D, Heredia-Pi, IB, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Htet, AS, Hu, G, Huang, H, Huang, JJ, Huntley, BM, Huynh, C, Iburg, KM, Ileanu, BV, Innos, K, Irenso, AA, Jahanmehr, N, Jakovljevic, MB, James, P, James, SL, Javanbakht, M, Jayaraman, SP, Jayatilleke, AU, Jeemon, P, Jha, V, John, D, Johnson, C, Johnson, SC, Jonas, JB, Juel, K, Kabir, Z, Kalkonde, Y, Kamal, R, Kan, H, Karch, A, Karema, CK, Karimi, SM, Kasaeian, A, Kassebaum, NJ, Kastor, A, Katikireddi, SV, Kazanjan, K, Keiyoro, PN, Kemmer, L, Kemp, AH, Kengne, AP, Kerbo, AA, Kereselidze, M, Kesavachandran, CN, Khader, YS, Khalil, I, Khan, AR, Khan, EA, Khan, G, Khang, Y-H, Khoja, ATA, Khonelidze, I, Khubchandani, J, Kibret, GD, Kim, D, Kim, P, Kim, YJ, Kimokoti, RW, Kinfu, Y, Kissoon, N, Kivipelto, M, Kokubo, Y, Kolk, A, Kolte, D, Kopec, JA, Kosen, S, Koul, PA, Koyanagi, A, Kravchenko, M, Krishnaswami, S, Krohn, KJ, Defo, BK, Bicer, BK, Kuipers, EJ, Kulkarni, VS, Kumar, GA, Kumsa, FA, Kutz, M, Kyu, HH, Lager, ACJ, Lal, A, Lal, DK, Lalloo, R, Lallukka, T, Lan, Q, Langan, SM, Lansingh, VC, Larson, HJ, Larsson, A, Laryea, DO, Latif, AA, Lawrynowicz, AEB, Leasher, JL, Leigh, J, Leinsalu, M, Leshargie, CT, Leung, J, Leung, R, Levi, M, Liang, X, Lim, SS, Lind, M, Linn, S, Lipshultz, SE, Liu, P, Liu, Y, Lo, L-T, Logroscino, G, Lopez, AD, Lorch, SA, Lotufo, PA, Lozano, R, Lunevicius, R, Lyons, RA, Macarayan, ERK, Mackay, MT, El Razek, HMA, El Razek, MMA, Mahdavi, M, Majeed, A, Malekzadeh, R, Malta, DC, Mantovani, LG, Manyazewal, T, Mapoma, CC, Marcenes, W, Marks, GB, Marquez, N, Martinez-Raga, J, Marzan, MB, Massano, J, Mathur, MR, Maulik, PK, Mazidi, M, McAlinden, C, McGrath, JJ, McNellan, C, Meaney, PA, Mehari, A, Mehndiratta, MM, Meier, T, Mekonnen, AB, Meles, KG, Memish, ZA, Mengesha, MM, Mengiste, DT, Mengistie, MA, Menota, BG, Mensah, GA, Mereta, ST, Meretoja, A, Meretoja, TJ, Mezgebe, HB, Micha, R, Millear, A, Mills, EJ, Minnig, S, Mirarefin, M, Mirrakhimov, EM, Mock, CN, Mohammad, KA, Mohammed, S, Mohanty, SK, Mokdad, AH, Mola, GLD, Molokhia, M, Monasta, L, Montico, M, Moradi-Lakeh, M, Moraga, P, Morawska, L, Mori, R, Moses, M, Mueller, UO, Murthy, S, Musa, KI, Nachega, JB, Nagata, C, Nagel, G, Naghavi, M, Naheed, A, Naldi, L, Nangia, V, Nascimento, BR, Negoi, I, Neupane, SP, Newton, CR, Ng, M, Ngalesoni, FN, Ngunjiri, JW, Nguyen, G, Ningrum, DNA, Nolte, S, Nomura, M, Norheim, OF, Norrving, B, Noubiap, JJN, Obermeyer, CM, Ogbo, FA, Oh, I-H, Okoro, A, Oladimeji, O, Olagunju, AT, Olivares, PR, Olsen, HE, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ortiz, A, Osborne, RH, Osman, M, Owolabi, MO, PA, M, Pain, AW, Pakhale, S, Castillo, EP, Pana, A, Papachristou, C, Parsaeian, M, Patel, T, Patton, GC, Paudel, D, Paul, VK, Pearce, N, Pereira, DM, Perez-Padilla, R, Perez-Ruiz, F, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pigott, DM, Pillay, JD, Pinho, C, Polinder, S, Pond, CD, Prakash, V, Purwar, M, Qorbani, M, Quistberg, DA, Radfar, A, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rai, RK, Ram, U, Rana, SM, Rankin, Z, Rao, PV, Rao, PC, Rawaf, S, Rego, MAS, Reitsma, M, Remuzzi, G, Renzaho, AMNN, Resnikoff, S, Rezaei, S, Rezai, MS, Ribeiro, AL, Roba, HS, Rokni, MB, Ronfani, L, Roshandel, G, Roth, GA, Rothenbacher, D, Roy, NK, Sachdev, PS, Sackey, BB, Saeedi, MY, Safiri, S, Sagar, R, Sahraian, MA, Saleh, MM, Salomon, JA, Samy, AM, Sanabria, JR, Sanchez-Niño, MD, Sandar, L, Santos, IS, Santos, JV, Milicevic, MMS, Sarmiento-Suarez, R, Sartorius, B, Satpathy, M, Savic, M, Sawhney, M, Saylan, MI, Schöttker, B, Schutte, AE, Schwebel, DC, Seedat, S, Seid, AM, Seifu, CN, Sepanlou, SG, Serdar, B, Servan-Mori, EE, Setegn, T, Shackelford, KA, Shaheen, A, Shahraz, S, Shaikh, MA, Shakh-Nazarova, M, Shamsipour, M, Islam, SMS, Sharma, J, Sharma, R, She, J, Sheikhbahaei, S, Shen, J, Shi, P, Shigematsu, M, Shin, M-J, Shiri, R, Shoman, H, Shrime, MG, Sibamo, ELS, Sigfusdottir, ID, Silva, DAS, Silveira, DGA, Sindi, S, Singh, A, Singh, JA, Singh, OP, Singh, PK, Singh, V, Sinke, AH, Sinshaw, AE, Skirbekk, V, Sliwa, K, Smith, A, Sobngwi, E, Soneji, S, Soriano, JB, Sousa, TCM, Sposato, LA, Sreeramareddy, CT, Stathopoulou, V, Steel, N, Steiner, C, Steinke, S, Stokes, MA, Stranges, S, Strong, M, Stroumpoulis, K, Sturua, L, Sufiyan, MB, Suliankatchi, RA, Sun, J, Sur, P, Swaminathan, S, Sykes, BL, Tabarés-Seisdedos, R, Tabb, KM, Taffere, GR, Talongwa, RT, Tarajia, M, Tavakkoli, M, Taveira, N, Teeple, S, Tegegne, TK, Tehrani-Banihashemi, A, Tekelab, T, Tekle, DY, Shifa, GT, Terkawi, AS, Tesema, AG, Thakur, JS, Thomson, AJ, Tillmann, T, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Tortajada, M, Troeger, C, Truelsen, T, Tura, AK, Uchendu, US, Ukwaja, KN, Undurraga, EA, Uneke, CJ, Uthman, OA, van Boven, JFM, Van Dingenen, R, Varughese, S, Vasankari, T, Venketasubramanian, N, Violante, FS, Vladimirov, SK, Vlassov, VV, Vollset, SE, Vos, T, Wagner, JA, Wakayo, T, Waller, SG, Walson, JL, Wang, H, Wang, Y-P, Watkins, DA, Weiderpass, E, Weintraub, RG, Wen, C-P, Werdecker, A, Wesana, J, Westerman, R, Whiteford, HA, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Won, S, Workicho, A, Workie, SB, Wubshet, M, Xavier, D, Xu, G, Yadav, AK, Yaghoubi, M, Yakob, B, Yan, LL, Yano, Y, Yaseri, M, Yimam, HH, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Zaidi, Z, El Sayed Zaki, M, Zambrana-Torrelio, C, Zapata, T, Zenebe, ZM, Zodpey, S, Zoeckler, L, Zuhlke, LJ, Murray, CJL, Barber, RM, Fullman, N, Sorensen, RJD, Bollyky, T, McKee, M, Nolte, E, Abajobir, AA, Abate, KH, Abbafati, C, Abbas, KM, Abd-Allah, F, Abdulle, AM, Abdurahman, AA, Abera, SF, Abraham, B, Abreha, GF, Adane, K, Adelekan, AL, Adetifa, IMO, Afshin, A, Agarwal, A, Agarwal, SK, Agarwal, S, Agrawal, A, Kiadaliri, AA, Ahmadi, A, Ahmed, KY, Ahmed, MB, Akinyemi, RO, 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Fereshtehnejad, S-M, Fernandes, JG, Fernandes, JC, Feyissa, TR, Fischer, F, Fitzmaurice, C, Fleming, TD, Foigt, N, Foreman, KJ, Forouzanfar, MH, Franklin, RC, Frostad, J, G/hiwot, TT, Gakidou, E, Gambashidze, K, Gamkrelidze, A, Gao, W, Garcia-Basteiro, AL, Gebre, T, Gebremedhin, AT, Gebremichael, MW, Gebru, AA, Gelaye, AA, Geleijnse, JM, Genova-Maleras, R, Gibney, KB, Giref, AZ, Gishu, MD, Giussani, G, Godwin, WW, Gold, A, Goldberg, EM, Gona, PN, Goodridge, A, Gopalani, SV, Goto, A, Graetz, N, Greaves, F, Griswold, M, Guban, PI, Gugnani, HC, Gupta, PC, Gupta, R, Gupta, T, Gupta, V, Habtewold, TD, Hafezi-Nejad, N, Haile, D, Hailu, AD, Hailu, GB, Hakuzimana, A, Hamadeh, RR, Hambisa, MT, Hamidi, S, Hammami, M, Hankey, GJ, Hao, Y, Harb, HL, Hareri, HA, Haro, JM, Hassanvand, MS, Havmoeller, R, Hay, RJ, Hay, SI, Hendrie, D, Heredia-Pi, IB, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Htet, AS, Hu, G, Huang, H, Huang, JJ, Huntley, BM, Huynh, C, Iburg, KM, Ileanu, BV, Innos, K, Irenso, AA, 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Leshargie, CT, Leung, J, Leung, R, Levi, M, Liang, X, Lim, SS, Lind, M, Linn, S, Lipshultz, SE, Liu, P, Liu, Y, Lo, L-T, Logroscino, G, Lopez, AD, Lorch, SA, Lotufo, PA, Lozano, R, Lunevicius, R, Lyons, RA, Macarayan, ERK, Mackay, MT, El Razek, HMA, El Razek, MMA, Mahdavi, M, Majeed, A, Malekzadeh, R, Malta, DC, Mantovani, LG, Manyazewal, T, Mapoma, CC, Marcenes, W, Marks, GB, Marquez, N, Martinez-Raga, J, Marzan, MB, Massano, J, Mathur, MR, Maulik, PK, Mazidi, M, McAlinden, C, McGrath, JJ, McNellan, C, Meaney, PA, Mehari, A, Mehndiratta, MM, Meier, T, Mekonnen, AB, Meles, KG, Memish, ZA, Mengesha, MM, Mengiste, DT, Mengistie, MA, Menota, BG, Mensah, GA, Mereta, ST, Meretoja, A, Meretoja, TJ, Mezgebe, HB, Micha, R, Millear, A, Mills, EJ, Minnig, S, Mirarefin, M, Mirrakhimov, EM, Mock, CN, Mohammad, KA, Mohammed, S, Mohanty, SK, Mokdad, AH, Mola, GLD, Molokhia, M, Monasta, L, Montico, M, Moradi-Lakeh, M, Moraga, P, Morawska, L, Mori, R, Moses, M, Mueller, UO, Murthy, S, Musa, KI, Nachega, JB, Nagata, C, Nagel, G, Naghavi, M, Naheed, A, Naldi, L, Nangia, V, Nascimento, BR, Negoi, I, Neupane, SP, Newton, CR, Ng, M, Ngalesoni, FN, Ngunjiri, JW, Nguyen, G, Ningrum, DNA, Nolte, S, Nomura, M, Norheim, OF, Norrving, B, Noubiap, JJN, Obermeyer, CM, Ogbo, FA, Oh, I-H, Okoro, A, Oladimeji, O, Olagunju, AT, Olivares, PR, Olsen, HE, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ortiz, A, Osborne, RH, Osman, M, Owolabi, MO, PA, M, Pain, AW, Pakhale, S, Castillo, EP, Pana, A, Papachristou, C, Parsaeian, M, Patel, T, Patton, GC, Paudel, D, Paul, VK, Pearce, N, Pereira, DM, Perez-Padilla, R, Perez-Ruiz, F, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pigott, DM, Pillay, JD, Pinho, C, Polinder, S, Pond, CD, Prakash, V, Purwar, M, Qorbani, M, Quistberg, DA, Radfar, A, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rai, RK, Ram, U, Rana, SM, Rankin, Z, Rao, PV, Rao, PC, Rawaf, S, Rego, MAS, Reitsma, M, Remuzzi, G, Renzaho, AMNN, Resnikoff, S, Rezaei, S, Rezai, MS, Ribeiro, AL, Roba, HS, Rokni, MB, Ronfani, L, Roshandel, G, Roth, GA, Rothenbacher, D, Roy, NK, Sachdev, PS, Sackey, BB, Saeedi, MY, Safiri, S, Sagar, R, Sahraian, MA, Saleh, MM, Salomon, JA, Samy, AM, Sanabria, JR, Sanchez-Niño, MD, Sandar, L, Santos, IS, Santos, JV, Milicevic, MMS, Sarmiento-Suarez, R, Sartorius, B, Satpathy, M, Savic, M, Sawhney, M, Saylan, MI, Schöttker, B, Schutte, AE, Schwebel, DC, Seedat, S, Seid, AM, Seifu, CN, Sepanlou, SG, Serdar, B, Servan-Mori, EE, Setegn, T, Shackelford, KA, Shaheen, A, Shahraz, S, Shaikh, MA, Shakh-Nazarova, M, Shamsipour, M, Islam, SMS, Sharma, J, Sharma, R, She, J, Sheikhbahaei, S, Shen, J, Shi, P, Shigematsu, M, Shin, M-J, Shiri, R, Shoman, H, Shrime, MG, Sibamo, ELS, Sigfusdottir, ID, Silva, DAS, Silveira, DGA, Sindi, S, Singh, A, Singh, JA, Singh, OP, Singh, PK, Singh, V, Sinke, AH, Sinshaw, AE, Skirbekk, V, Sliwa, K, Smith, A, Sobngwi, E, Soneji, S, Soriano, JB, Sousa, TCM, Sposato, LA, Sreeramareddy, CT, Stathopoulou, V, Steel, N, Steiner, C, Steinke, S, Stokes, MA, Stranges, S, Strong, M, Stroumpoulis, K, Sturua, L, Sufiyan, MB, Suliankatchi, RA, Sun, J, Sur, P, Swaminathan, S, Sykes, BL, Tabarés-Seisdedos, R, Tabb, KM, Taffere, GR, Talongwa, RT, Tarajia, M, Tavakkoli, M, Taveira, N, Teeple, S, Tegegne, TK, Tehrani-Banihashemi, A, Tekelab, T, Tekle, DY, Shifa, GT, Terkawi, AS, Tesema, AG, Thakur, JS, Thomson, AJ, Tillmann, T, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Tortajada, M, Troeger, C, Truelsen, T, Tura, AK, Uchendu, US, Ukwaja, KN, Undurraga, EA, Uneke, CJ, Uthman, OA, van Boven, JFM, Van Dingenen, R, Varughese, S, Vasankari, T, Venketasubramanian, N, Violante, FS, Vladimirov, SK, Vlassov, VV, Vollset, SE, Vos, T, Wagner, JA, Wakayo, T, Waller, SG, Walson, JL, Wang, H, Wang, Y-P, Watkins, DA, Weiderpass, E, Weintraub, RG, Wen, C-P, Werdecker, A, Wesana, J, Westerman, R, Whiteford, HA, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Won, S, Workicho, A, Workie, SB, Wubshet, M, Xavier, D, Xu, G, Yadav, AK, Yaghoubi, M, Yakob, B, Yan, LL, Yano, Y, Yaseri, M, Yimam, HH, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Zaidi, Z, El Sayed Zaki, M, Zambrana-Torrelio, C, Zapata, T, Zenebe, ZM, Zodpey, S, Zoeckler, L, Zuhlke, LJ, and Murray, CJL
Published: 2017

7. The burden of mental disorders in the eastern mediterranean region, 1990-2013

Author: Charara, R, Forouzanfar, M, Naghavi, M, Moradi-Lakeh, M, Afshin, A, Vos, T, Daoud, F, Wang, H, Bcheraoui, CE, Khalil, I, Hamadeh, RR, Khosravi, A, Rahimi-Movaghar, V, Khader, Y, Al-Hamad, N, Obermeyer, CM, Rafay, A, Asghar, R, Rana, SM, Shaheen, A, Abu-Rmeileh, NME, Husseini, A, Abu-Raddad, LJ, Khoja, T, Rayess, ZAA, AlBuhairan, FS, Hsairi, M, Alomari, MA, Ali, R, Roshandel, G, Terkawi, AS, Hamidi, S, Refaat, AH, Westerman, R, Kiadaliri, AA, Akanda, AS, Ali, SD, Bacha, U, Badawi, A, Bazargan-Hejazi, S, Faghmous, IAD, Fereshtehnejad, SM, Fischer, F, Jonas, JB, Defo, BK, Mehari, A, Omer, SB, Pourmalek, F, Uthman, OA, Mokdad, AA, Maalouf, FT, Abd-Allah, F, Akseer, N, Arya, D, Borschmann, R, Brazinova, A, Brugha, TS, Catala-Lopez, F, Degenhardt, L, Ferrari, A, Haro, JM, Horino, M, Hornberger, JC, Huang, H, Kieling, C, Kim, D, Kim, Y, Knudsen, AK, Mitchell, PB, Patton, G, Sagar, R, Satpathy, M, Savuon, K, Seedat, S, Shiue, I, Skogen, JC, Stein, DJ, Tabb, KM, Whiteford, HA, Yip, P, Yonemoto, N, Murray, CJL, Mokdad, AH, Charara, R, Forouzanfar, M, Naghavi, M, Moradi-Lakeh, M, Afshin, A, Vos, T, Daoud, F, Wang, H, Bcheraoui, CE, Khalil, I, Hamadeh, RR, Khosravi, A, Rahimi-Movaghar, V, Khader, Y, Al-Hamad, N, Obermeyer, CM, Rafay, A, Asghar, R, Rana, SM, Shaheen, A, Abu-Rmeileh, NME, Husseini, A, Abu-Raddad, LJ, Khoja, T, Rayess, ZAA, AlBuhairan, FS, Hsairi, M, Alomari, MA, Ali, R, Roshandel, G, Terkawi, AS, Hamidi, S, Refaat, AH, Westerman, R, Kiadaliri, AA, Akanda, AS, Ali, SD, Bacha, U, Badawi, A, Bazargan-Hejazi, S, Faghmous, IAD, Fereshtehnejad, SM, Fischer, F, Jonas, JB, Defo, BK, Mehari, A, Omer, SB, Pourmalek, F, Uthman, OA, Mokdad, AA, Maalouf, FT, Abd-Allah, F, Akseer, N, Arya, D, Borschmann, R, Brazinova, A, Brugha, TS, Catala-Lopez, F, Degenhardt, L, Ferrari, A, Haro, JM, Horino, M, Hornberger, JC, Huang, H, Kieling, C, Kim, D, Kim, Y, Knudsen, AK, Mitchell, PB, Patton, G, Sagar, R, Satpathy, M, Savuon, K, Seedat, S, Shiue, I, Skogen, JC, Stein, DJ, Tabb, KM, Whiteford, HA, Yip, P, Yonemoto, N, Murray, CJL, and Mokdad, AH
Abstract: © 2017 Charara et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The Eastern Mediterranean Region (EMR) is witnessing an increase in chronic disorders, including mental illness. With ongoing unrest, this is expected to rise. This is the first study to quantify the burden of mental disorders in the EMR. We used data from the Global Burden of Disease study (GBD) 2013. DALYs (disability-adjusted life years) allow assessment of both premature mortality (years of life lost-YLLs) and nonfatal outcomes (years lived with disability-YLDs). DALYs are computed by adding YLLs and YLDs for each age-sex-country group. In 2013, mental disorders contributed to 5.6% of the total disease burden in the EMR (1894 DALYS/100,000 population): 2519 DALYS/100,000 (2590/100,000 males, 2426/100,000 females) in high-income countries, 1884 DALYS/100,000 (1618/100,000 males, 2157/100,000 females) in middle-income countries, 1607 DALYS/100,000 (1500/100,000 males, 1717/100,000 females) in low-income countries. Females had a greater proportion of burden due to mental disorders than did males of equivalent ages, except for those under 15 years of age. The highest proportion of DALYs occurred in the 25-49 age group, with a peak in the 35-39 years age group (5344 DALYs/100,000). The burden of mental disorders Burden of Mental Disorders in EMR PLOS ONE in EMR increased from 1726 DALYs/100,000 in 1990 to 1912 DALYs/100,000 in 2013 (10.8% increase). Within the mental disorders group in EMR, depressive disorders accounted for most DALYs, followed by anxiety disorders. Among EMR countries, Palestine had the largest burden of mental disorders. Nearly all EMR countries had a higher mental disorder burden compared to the global level. Our findings call for EMR ministries of health to increase provision of mental health
Published: 2017

8. The Burden of Mental Disorders in the Eastern Mediterranean Region, 1990-2013

Author: Maulik, PK, Charara, R, Forouzanfar, M, Naghavi, M, Moradi-Lakeh, M, Afshin, A, Vos, T, Daoud, F, Wang, H, El Bcheraoui, C, Khalil, I, Hamadeh, RR, Khosravi, A, Rahimi-Movaghar, V, Khader, Y, Al-Hamad, N, Obermeyer, CM, Rafay, A, Asghar, R, Rana, SM, Shaheen, A, Abu-Rmeileh, NME, Husseini, A, Abu-Raddad, LJ, Khoja, T, Al Rayess, ZA, AlBuhairan, FS, Hsairi, M, Alomari, MA, Ali, R, Roshandel, G, Terkawi, AS, Hamidi, S, Refaat, AH, Westerman, R, Kiadaliri, AA, Akanda, AS, Ali, SD, Bacha, U, Badawi, A, Bazargan-Hejazi, S, Faghmous, IAD, Fereshtehnejad, S-M, Fischer, F, Jonas, JB, Defo, BK, Mehari, A, Omer, SB, Pourmalek, F, Uthman, OA, Mokdad, AA, Maalouf, FT, Abd-Allah, F, Akseer, N, Arya, D, Borschmann, R, Brazinova, A, Brugha, TS, Catala-Lopez, F, Degenhardt, L, Ferrari, A, Maria Haro, J, Horino, M, Hornberger, JC, Huang, H, Kieling, C, Kim, D, Kim, Y, Knudsen, AK, Mitchell, PB, Patton, G, Sagar, R, Satpathy, M, Savuon, K, Seedat, S, Shiuem, I, Skogen, JC, Stein, DJ, Tabb, KM, Whitefored, HA, Yip, P, Yonemoto, N, Murray, CJL, Mokdad, AH, Maulik, PK, Charara, R, Forouzanfar, M, Naghavi, M, Moradi-Lakeh, M, Afshin, A, Vos, T, Daoud, F, Wang, H, El Bcheraoui, C, Khalil, I, Hamadeh, RR, Khosravi, A, Rahimi-Movaghar, V, Khader, Y, Al-Hamad, N, Obermeyer, CM, Rafay, A, Asghar, R, Rana, SM, Shaheen, A, Abu-Rmeileh, NME, Husseini, A, Abu-Raddad, LJ, Khoja, T, Al Rayess, ZA, AlBuhairan, FS, Hsairi, M, Alomari, MA, Ali, R, Roshandel, G, Terkawi, AS, Hamidi, S, Refaat, AH, Westerman, R, Kiadaliri, AA, Akanda, AS, Ali, SD, Bacha, U, Badawi, A, Bazargan-Hejazi, S, Faghmous, IAD, Fereshtehnejad, S-M, Fischer, F, Jonas, JB, Defo, BK, Mehari, A, Omer, SB, Pourmalek, F, Uthman, OA, Mokdad, AA, Maalouf, FT, Abd-Allah, F, Akseer, N, Arya, D, Borschmann, R, Brazinova, A, Brugha, TS, Catala-Lopez, F, Degenhardt, L, Ferrari, A, Maria Haro, J, Horino, M, Hornberger, JC, Huang, H, Kieling, C, Kim, D, Kim, Y, Knudsen, AK, Mitchell, PB, Patton, G, Sagar, R, Satpathy, M, Savuon, K, Seedat, S, Shiuem, I, Skogen, JC, Stein, DJ, Tabb, KM, Whitefored, HA, Yip, P, Yonemoto, N, Murray, CJL, and Mokdad, AH
Abstract: The Eastern Mediterranean Region (EMR) is witnessing an increase in chronic disorders, including mental illness. With ongoing unrest, this is expected to rise. This is the first study to quantify the burden of mental disorders in the EMR. We used data from the Global Burden of Disease study (GBD) 2013. DALYs (disability-adjusted life years) allow assessment of both premature mortality (years of life lost-YLLs) and nonfatal outcomes (years lived with disability-YLDs). DALYs are computed by adding YLLs and YLDs for each age-sex-country group. In 2013, mental disorders contributed to 5.6% of the total disease burden in the EMR (1894 DALYS/100,000 population): 2519 DALYS/100,000 (2590/100,000 males, 2426/100,000 females) in high-income countries, 1884 DALYS/100,000 (1618/100,000 males, 2157/100,000 females) in middle-income countries, 1607 DALYS/100,000 (1500/100,000 males, 1717/100,000 females) in low-income countries. Females had a greater proportion of burden due to mental disorders than did males of equivalent ages, except for those under 15 years of age. The highest proportion of DALYs occurred in the 25-49 age group, with a peak in the 35-39 years age group (5344 DALYs/100,000). The burden of mental disorders in EMR increased from 1726 DALYs/100,000 in 1990 to 1912 DALYs/100,000 in 2013 (10.8% increase). Within the mental disorders group in EMR, depressive disorders accounted for most DALYs, followed by anxiety disorders. Among EMR countries, Palestine had the largest burden of mental disorders. Nearly all EMR countries had a higher mental disorder burden compared to the global level. Our findings call for EMR ministries of health to increase provision of mental health services and to address the stigma of mental illness. Moreover, our results showing the accelerating burden of mental health are alarming as the region is seeing an increased level of instability. Indeed, mental health problems, if not properly addressed, will lead to an increased burden of diseases
Published: 2017

9. Efficient Power Allocation for LDPC-Coded MIMO Systems

Author: K. Kishan Rao, M. Sushanth Bab, and Layak Ali Sd
Subjects: Computer science, Electronic engineering, Data_CODINGANDINFORMATIONTHEORY, Low-density parity-check code, Computer Science::Information Theory, Power (physics), Mimo systems
Abstract: In this papers an efficient ordering scheme for an ordered successive interference cancellation detector is determined under the bit error rate minimization criterion for multiple-input multiple-output(MIMO) communication systems using transmission power control. From the convexity of the Q-function, we evaluate the choice of suitable quantization characteristics for both the decoder messages and the received samples in Low Density Parity Check (LDPC)-coded systems using M-QAM schemes. We derive the ordering strategy that makes the channel gains converge to their geometric mean. Based on this approach, the fixed ordering algorithm is first designed, for which the geometric mean is used for a constant threshold using correlation among ordering results.
Published: 2011

10. Health in times of uncertainty in the eastern Mediterranean region, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Author: Mokdad, AH, Forouzanfar, MH, Daoud, F, El Bcheraoui, C, Moradi-Lakeh, M, Khalil, I, Afshin, A, Tuffaha, M, Charara, R, Barber, RM, Wagner, J, Cercy, K, Kravitz, H, Coates, MM, Robinson, M, Estep, K, Steiner, C, Jaber, S, Mokdad, AA, O'Rourke, KF, Chew, A, Kim, P, El Razek, MMA, Abdalla, S, Abd-Allah, F, Abraham, JP, Abu-Raddad, LJ, Abu-Rmeileh, NME, Al-Nehmi, AA, Akanda, AS, Al Ahmadi, H, Al Khabouri, MJ, Al Lami, FH, Al Rayess, ZA, Alasfoor, D, AlBuhairan, FS, Aldhahri, SF, Alghnam, S, Alhabib, S, Al-Hamad, N, Ali, R, Ali, SD, Alkhateeb, M, AlMazroa, MA, Alomari, MA, Al-Raddadi, R, Alsharif, U, Al-Sheyab, N, Alsowaidi, S, Al-Thani, M, Altirkawi, KA, Amare, AT, Amini, H, Ammar, W, Anwari, P, Asayesh, H, Asghar, R, Assabri, AM, Assadi, R, Bacha, U, Badawi, A, Bakfalouni, T, Basulaiman, MO, Bazargan-Hejazi, S, Bedi, N, Bhakta, AR, Bhutta, ZA, Bin Abdulhak, AA, Boufous, S, Bourne, RRA, Danawi, H, Das, J, Deribew, A, Ding, EL, Durrani, AM, Elshrek, Y, Ibrahim, ME, Eshrati, B, Esteghamati, A, Faghmous, IAD, Farzadfar, F, Feigl, AB, Fereshtehnejad, SM, Filip, I, Fischer, F, Gankpé, FG, Ginawi, I, Mokdad, AH, Forouzanfar, MH, Daoud, F, El Bcheraoui, C, Moradi-Lakeh, M, Khalil, I, Afshin, A, Tuffaha, M, Charara, R, Barber, RM, Wagner, J, Cercy, K, Kravitz, H, Coates, MM, Robinson, M, Estep, K, Steiner, C, Jaber, S, Mokdad, AA, O'Rourke, KF, Chew, A, Kim, P, El Razek, MMA, Abdalla, S, Abd-Allah, F, Abraham, JP, Abu-Raddad, LJ, Abu-Rmeileh, NME, Al-Nehmi, AA, Akanda, AS, Al Ahmadi, H, Al Khabouri, MJ, Al Lami, FH, Al Rayess, ZA, Alasfoor, D, AlBuhairan, FS, Aldhahri, SF, Alghnam, S, Alhabib, S, Al-Hamad, N, Ali, R, Ali, SD, Alkhateeb, M, AlMazroa, MA, Alomari, MA, Al-Raddadi, R, Alsharif, U, Al-Sheyab, N, Alsowaidi, S, Al-Thani, M, Altirkawi, KA, Amare, AT, Amini, H, Ammar, W, Anwari, P, Asayesh, H, Asghar, R, Assabri, AM, Assadi, R, Bacha, U, Badawi, A, Bakfalouni, T, Basulaiman, MO, Bazargan-Hejazi, S, Bedi, N, Bhakta, AR, Bhutta, ZA, Bin Abdulhak, AA, Boufous, S, Bourne, RRA, Danawi, H, Das, J, Deribew, A, Ding, EL, Durrani, AM, Elshrek, Y, Ibrahim, ME, Eshrati, B, Esteghamati, A, Faghmous, IAD, Farzadfar, F, Feigl, AB, Fereshtehnejad, SM, Filip, I, Fischer, F, Gankpé, FG, and Ginawi, I
Abstract: © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license Background The eastern Mediterranean region is comprised of 22 countries: Afghanistan, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pakistan, Palestine, Qatar, Saudi Arabia, Somalia, Sudan, Syria, Tunisia, the United Arab Emirates, and Yemen. Since our Global Burden of Disease Study 2010 (GBD 2010), the region has faced unrest as a result of revolutions, wars, and the so-called Arab uprisings. The objective of this study was to present the burden of diseases, injuries, and risk factors in the eastern Mediterranean region as of 2013. Methods GBD 2013 includes an annual assessment covering 188 countries from 1990 to 2013. The study covers 306 diseases and injuries, 1233 sequelae, and 79 risk factors. Our GBD 2013 analyses included the addition of new data through updated systematic reviews and through the contribution of unpublished data sources from collaborators, an updated version of modelling software, and several improvements in our methods. In this systematic analysis, we use data from GBD 2013 to analyse the burden of disease and injuries in the eastern Mediterranean region specifically. Findings The leading cause of death in the region in 2013 was ischaemic heart disease (90·3 deaths per 100 000 people), which increased by 17·2% since 1990. However, diarrhoeal diseases were the leading cause of death in Somalia (186·7 deaths per 100 000 people) in 2013, which decreased by 26·9% since 1990. The leading cause of disability-adjusted life-years (DALYs) was ischaemic heart disease for males and lower respiratory infection for females. High blood pressure was the leading risk factor for DALYs in 2013, with an increase of 83·3% since 1990. Risk factors for DALYs varied by country. In low-income countries, childhood wasting was the leading cause of DALYs in Afghanistan, Somalia, and Yemen, whereas unsafe sex was the leading ca
Published: 2016

11. Mobile Adhoc Network (MANET) Routing Protocols Analytical Study

Author: Sd Salman Ali, Sd Salman Ali, primary
Published: 2013
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12. Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016

Author: Nancy, Fullman, Jamal, Yearwood, Solomon, M, Abay, Cristiana, Abbafati, Foad, Abd-Allah, Jemal, Abdela, Ahmed, Abdelalim, Zegeye, Abebe, Teshome, Abuka, Abebo, Victor, Aboyans, Haftom, Niguse, Abraha, Daisy, M, X, Abreu, Laith, Abu-Raddad, J, Akilew, Awoke, Adane, Rufus, Adesoji, Adedoyin, Olatunji, Adetokunboh, Tara, Ballav, Adhikari, Mohsen, Afarideh, Ashkan, Afshin, Gina, Agarwal, Dominic, Agius, Anurag, Agrawal, Sutapa, Agrawal, Aliasghar, Ahmad, Kiadaliri, Miloud, Taki, Eddine, Aichour, Mohammed, Akibu, Rufus, Olusola, Akinyemi, Tomi, Akinyemiju, F, Nadia, Akseer, Faris, Hasan, Lami, Al, Fares, Alahdab, Ziyad, Al-Aly, Khurshid, Alam, Tahiya, Alam, Deena, Alasfoor, Mohammed, I, Albittar, Kefyalew, Addis, Alene, Ayman, Al-Eyadhy, Syed, Danish, Ali, Mehran, Alijanzadeh, Syed, M, Aljunid, Ala’A, Alkerwi, François, Alla, Peter, Allebeck, Christine, Allen, Mahmoud, A, Alomari, Rajaa, Al-Raddadi, Ubai, Alsharif, Khalid, A, Altirkawi, Nelson, Alvis-Guzman, Azmeraw, T, Amare, Kebede, Amenu, Walid, Ammar, Yaw, Ampem, Amoako, Nahla, Anber, Catalina, Liliana, Andrei, Sofia, Androudi, Carl, Abelardo, Antonio, T, Valdelaine, E, Araújo, M, Olatunde, Aremu, Johan, Ärnlöv, Artaman, Al, Krishna, Kumar, Aryal, Hamid, Asayesh, Ephrem, Tsegay, Asfaw, Solomon, Weldegebreal, Asgedom, Rana, Jawad, Asghar, Mengistu, Mitiku, Ashebir, Netsanet, Abera, Asseffa, Tesfay, Mehari, Atey, Sachin, R, Atre, Madhu, Atteraya, S, Leticia, Avila-Burgos, Euripide, Frinel, Arthur, G, Avokpaho, Ashish, Awasthi, Beatriz, Paulina, Ayala, Quintanilla, Animut, Alebel, Ayalew, Henok, Tadesse, Ayele, Rakesh, Ayer, Tambe, Betrand, Ayuk, Peter, Azzopardi, Natasha, Azzopardi-Muscat, Tesleem, Kayode, Babalola, Hamid, Badali, Alaa, Badawi, Maciej, Banach, Amitava, Banerjee, Amrit, Banstola, Ryan, M, Barber, Miguel, Barboza, A, Suzanne, L, Barker-Collo, Till, Bärnighausen, Simon, Barquera, Lope, H, Barrero, Quique, Bassat, Sanjay, Basu, Bernhard, T, Baune, Shahrzad, Bazargan-Hejazi, Neeraj, Bedi, Ettore, Beghi, Masoud, Behzadifar, Meysam, Behzadifar, Bayu, Begashaw, Bekele, Abate, Bekele, Belachew, Saba, Abraham, Belay, Yihalem, Abebe, Belay, Michelle, L, Bell, Aminu, Bello, K, Derrick, A, Bennett, James, Bennett, R, Isabela, M, Bensenor, Derbew, Fikadu, Berhe, Eduardo, Bernabé, Robert, Steven, Bernstein, Mircea, Beuran, Ashish, Bhalla, Paurvi, Bhatt, Soumyadeep, Bhaumik, Zulfiqar, A, Bhutta, Belete, Biadgo, Ali, Bijani, Boris, Bikbov, Charles, Birungi, Stan, Biryukov, Hailemichael, Bizuneh, Ian, W, Bolliger, Kaylin, Bolt, Ibrahim, R, Bou-Orm, Kayvan, Bozorgmehr, Oliver, Jerome, Brady, Alexandra, Brazinova, Nicholas, J, Breitborde, K, Hermann, Brenner, Gabrielle, Britton, Traolach, S, Brugha, Zahid, Butt, A, Lucero, Cahuana-Hurtado, Ismael, Ricardo, Campos-Nonato, Julio, Cesar, Campuzano, Josip, Car, Mate, Car, Rosario, Cárdenas, Juan, Jesus, Carrero, Felix, Carvalho, Carlos, A, Castañeda-Orjuela, Jacqueline, Castillo, Rivas, Ferrán, Catalá-López, Kelly, Cercy, Julian, Chalek, Hsing-Yi, Chang, Jung-Chen, Chang, Aparajita, Chattopadhyay, Pankaj, Chaturvedi, Peggy, Pei-Chia, Chiang, Vesper, Hichilombwe, Chisumpa, Jee-Young, J, Choi, Hanne, Christensen, Devasahayam, Jesudas, Christopher, Sheng-Chia, Chung, Liliana, G, Ciobanu, Cirillo, Massimo, Danny, Colombara, Sara, Conti, Cyrus, Cooper, Leslie, Cornaby, Paolo, Angelo, Cortesi, Monica, Cortinovis, Alexandre, Costa, Pereira, Ewerton, Cousin, Michael, H, Criqui, Elizabeth, Cromwell, A, Christopher, Stephen, Crowe, John, Crump, A, Alemneh, Kabeta, Daba, Berihun, Assefa, Dachew, Abel, Fekadu, Dadi, Lalit, Dandona, Rakhi, Dandona, Paul, I, Dargan, Ahmad, Daryani, Maryam, Daryani, Jai, Das, Siddharth, Kumar, Das, José, Das, Neves, Nicole, Davis, Weaver, Kairat, Davletov, Barbora, De, Courten, Diego, Leo, De, Jan-Walter, De, Neve, Robert, Dellavalle, P, Gebre, Demoz, Kebede, Deribe, Don, C, Des, Jarlais, Subhojit, Dey, Samath, D, Dharmaratne, Meghnath, Dhimal, Shirin, Djalalinia, David, Teye, Doku, Kate, Dolan, Ray, E, Dorsey, Kadine, Priscila, Bender, Dos, Santos, Kerrie, E, Doyle, Tim, Driscoll, R, Manisha, Dubey, Eleonora, Dubljanin, Bruce, Bartholow, Duncan, Michelle, Echko, Dumessa, Edessa, David, Edvardsson, Joshua, R, Ehrlich, Erika, Eldrenkamp, Ziad, El-Khatib, Matthias, Endres, Aman, Yesuf, Endries, Babak, Eshrati, Sharareh, Eskandarieh, Alireza, Esteghamati, Mahdi, Fakhar, Tamer, Farag, Mahbobeh, Faramarzi, Emerito, Jose, Aquino, Faraon, André, Faro, Farshad, Farzadfar, Adesegun, Fatusi, Mir, Sohail, Fazeli, Valery, Feigin, L, Andrea, B, Feigl, Netsanet, Fentahun, Seyed-Mohammad, Fereshtehnejad, Eduarda, Fernandes, João, C, Fernandes, Daniel, Obadare, Fijabi, Irina, Filip, Florian, Fischer, Christina, Fitzmaurice, Abraham, D, Flaxman, Luisa, Sorio, Flor, Nataliya, Foigt, Kyle, J, Foreman, Joseph, Frostad, J, Thomas, Fürst, Neal, D, Futran, Emmanuela, Gakidou, Silvano, Gallus, Ketevan, Gambashidze, Amiran, Gamkrelidze, Morsaleh, Ganji, Abadi, Kahsu, Gebre, Tsegaye, Tewelde, Gebrehiwot, Amanuel, Tesfay, Gebremedhin, Yalemzewod, Assefa, Gelaw, Johanna, M, Geleijnse, Demeke, Geremew, Peter, W, Gething, Reza, Ghadimi, Khalil, Ghasemi, Falavarjani, Maryam, Ghasemi-Kasman, Paramjit, Singh, Gill, Ababi, Zergaw, Giref, Maurice, Giroud, Melkamu, Dedefo, Gishu, Giorgia, Giussani, William, W, Godwin, Srinivas, Goli, Hector, Gomez-Dantes, Philimon, N, Gona, Amador, Goodridge, Sameer, Vali, Gopalani, Yevgeniy, Goryakin, Alessandra, Carvalho, Goulart, Ayman, Grada, Max, Griswold, Giuseppe, Grosso, Harish, Chander, Gugnani, Yuming, Guo, Rahul, Gupta, Rajeev, Gupta, Tanush, Gupta, Tarun, Gupta, Vipin, Gupta, Juanita, A, Haagsma, Vladimir, Hachinski, Nima, Hafezi-Nejad, Gessessew, Bugssa, Hailu, Randah, Ribhi, Hamadeh, Samer, Hamidi, Graeme, J, Hankey, Hilda, Harb, L, Heather, C, Harewood, Sivadasanpillai, Harikrishnan, Josep, Maria, Haro, Hamid, Yimam, Hassen, Rasmus, Havmoeller, Caitlin, Hawley, Simon, I, Hay, Jiawei, He, Stephen, J, Hearps, C, Mohamed, I, Hegazy, Behzad, Heibati, Mohsen, Heidari, Delia, Hendrie, Nathaniel, J, Henry, Victor, Hugo, Herrera, Ballesteros, Claudiu, Herteliu, Desalegn, Tsegaw, Hibstu, Molla, Kahssay, Hiluf, Hans, W, Hoek, Enayatollah, Homaie, Rad, Nobuyuki, Horita, Dean, H, Hosgood, Mostafa, Hosseini, Seyed, Reza, Hosseini, Mihaela, Hostiuc, Sorin, Hostiuc, Damian, G, Hoy, Mohamed, Hsairi, Aung, Soe, Htet, Guoqing, Hu, John, J, Huang, Kim, Moesgaard, Iburg, Fachmi, Idris, Ehimario, Uche, Igumbor, Chad, Ikeda, Bogdan, Vasile, Ileanu, Olayinka, Ilesanmi, S, Kaire, Innos, Seyed, Sina, Naghibi, Irvani, Caleb, M, Irvine, S, Farhad, Islami, Troy, A, Jacobs, Kathryn, Jacobsen, H, Nader, Jahanmehr, Rajesh, Jain, Sudhir, Kumar, Jain, Mihajlo, Jakovljevic, M, Moti, Tolera, Jalu, Amr, Jamal, A, Mehdi, Javanbakht, Achala, Upendra, Jayatilleke, Panniyammakal, Jeemon, Ravi, Prakash, Jha, Vivekanand, Jha, Jacek, Józwiak, Oommen, John, Sarah, Charlotte, Johnson, Jost, Jonas, B, Vasna, Joshua, Mikk, Jürisson, Zubair, Kabir, Rajendra, Kadel, Amaha, Kahsay, Rizwan, Kalani, Chittaranjan, Kar, Marina, Karanikolos, André, Karch, Corine, Kakizi, Karema, Seyed, Karimi, M, Amir, Kasaeian, Dessalegn, Haile, Kassa, Getachew, Mullu, Kassa, Tesfaye, Dessale, Kassa, Nicholas, Kassebaum, J, Srinivasa, Vittal, Katikireddi, Anil, Kaul, Norito, Kawakami, Konstantin, Kazanjan, Seifu, Kebede, Peter, Njenga, Keiyoro, Grant, Rodgers, Kemp, Andre, Pascal, Kengne, Maia, Kereselidze, Ezra, Belay, Ketema, Yousef, Saleh, Khader, Morteza, Abdullatif, Khafaie, Alireza, Khajavi, Ibrahim, A, Khalil, Ejaz, Ahmad, Khan, Gulfaraz, Khan, Nuruzzaman, Md, Khan, Muhammad, Ali, Khan, Mukti, Nath, Khanal, Young-Ho, Khang, Mona, M, Khater, Abdullah, Tawfih, Abdullah, Khoja, Ardeshir, Khosravi, Jagdish, Khubchandani, Getiye, Dejenu, Kibret, Daniel, Ngari, Kiirithio, Daniel, Kim, Yun, Jin, Kim, Ruth, Kimokoti, W, Yohannes, Kinfu, Sanjay, Kinra, Adnan, Kisa, Niranjan, Kissoon, Sonali, Kochhar, Yoshihiro, Kokubo, Jacek, A, Kopec, Soewarta, Kosen, Parvaiz, A, Koul, Koyanagi, Ai, Michael, Kravchenko, Kewal, Krishan, Kristopher, J, Krohn, Barthelemy, Kuate, Defo, Anil, G, Kumar, Pushpendra, Kumar, Michael, Kutz, Igor, Kuzin, Hmwe, H, Kyu, Deepesh, Pravinkumar, Lad, Alessandra, Lafranconi, Dharmesh, Kumar, Lal, Ratilal, Lalloo, Hilton, Lam, Qing, Lan, Justin, J, Lang, Van, Lansingh, C, Sonia, Lansky, Anders, Larsson, Arman, Latifi, Jeffrey, Victor, Lazarus, Janet, Leasher, L, Paul, H, Lee, Yirga, Legesse, James, Leigh, Cheru, Tesema, Leshargie, Samson, Leta, Janni, Leung, Ricky, Leung, Miriam, Levi, Yongmei, Li, Juan, Liang, Misgan, Legesse, Liben, Lee-Ling, Lim, Stephen, S, Lim, Margaret, Lind, Shai, Linn, Stefan, Listl, Patrick, Y, Liu, Shiwei, Liu, Rakesh, Lodha, Alan, D, Lopez, Scott, Lorch, A, Stefan, Lorkowski, Paulo, A, Lotufo, Timothy, C, D, Lucas, Raimundas, Lunevicius, Grégoire, Lurton, Ronan, A, Lyons, Fadi, Maalouf, Erlyn, Rachelle, King, Macarayan, Mark, T, Mackay, Emilie, Maddison, R, Fabiana, Madotto, Hassan, Magdy, Abd, El, Razek, 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Sd, Aljunid, Sm, Alomari, Ma, Altirkawi, Ka, Amare, At, Amoako, Ya, Andrei, Cl, Antonio, Cat, Araújo, Vem, Aryal, Kk, Asfaw, Et, Asgedom, Sw, Asghar, Rj, Ashebir, Mm, Asseffa, Na, Atey, Tm, Atre, Sr, Avokpaho, Efga, Ayala Quintanilla, Bp, Ayalew, Aa, Ayele, Ht, Ayuk, Tb, Babalola, Tk, Barber, Rm, Barboza, Ma, Barker-Collo, Sl, Barrero, Lh, Baune, Bt, Bekele, Bb, Belachew, Ab, Belay, Sa, Belay, Ya, Bell, Ml, Bello, Ak, Bennett, Da, Bennett, Jr, Bensenor, Im, Berhe, Df, Bhutta, Za, Bolliger, Iw, Bou-Orm, Ir, Brady, Oj, Breitborde, Njk, Butt, Za, Campos-Nonato, Ir, Campuzano, Jc, Carrero, Jj, Castañeda-Orjuela, Ca, Chang, Hy, Chang, Jc, Chiang, Pp, Chisumpa, Vh, Choi, Jj, Christopher, Dj, Chung, Sc, Ciobanu, Lg, Cortesi, Pa, Criqui, Mh, Cromwell, Ea, Crump, Ja, Daba, Ak, Dachew, Ba, Dadi, Af, Dargan, Pi, Das, Sk, De Neve, Jw, Dellavalle, Rp, Des Jarlais, Dc, Dharmaratne, Sd, Doku, Dt, Dorsey, Er, Dos Santos, Kpb, Doyle, Ke, Driscoll, Tr, Duncan, Bb, Ehrlich, Jr, El-Khatib, Zz, Endries, Ay, Faraon, Eja, Feigin, Vl, Feigl, Ab, Fereshtehnejad, Sm, Fernandes, Jc, Fijabi, Do, Flaxman, Ad, Foreman, Kj, Frostad, Jj, Futran, Nd, Gebre, Ak, Gebrehiwot, Tt, Gebremedhin, At, Gelaw, Ya, Geleijnse, Jm, Gething, Pw, Giref, Az, Gishu, Md, Godwin, Ww, Gona, Pn, Gopalani, Sv, Goulart, Ac, Gugnani, Hc, Haagsma, Ja, Hailu, Gb, Hamadeh, Rr, Hankey, Gj, Harb, Hl, Harewood, Hc, Haro, Jm, Hassen, Hy, Hay, Si, Hearps, Sjc, Hegazy, Mi, Henry, Nj, Herrera Ballesteros, Vh, Hibstu, Dt, Hiluf, Mk, Hoek, Hw, Hosgood, Hd, Hosseini, Sr, Hoy, Dg, Huang, Jj, Iburg, Km, Igumbor, Eu, Ileanu, Bv, Irvani, Ssn, Irvine, Cm, Jacobs, Ta, Jacobsen, Kh, Jain, Sk, Jakovljevic, Mb, Jalu, Mt, Jamal, Aa, Jayatilleke, Au, Jha, Rp, Johnson, Sc, Jonas, Jb, Karema, Ck, Karimi, Sm, Kassa, Dh, Kassa, Gm, Kassa, Td, Kassebaum, Nj, Katikireddi, Sv, Keiyoro, Pn, Kemp, Gr, Kengne, Ap, Ketema, Eb, Khafaie, Ma, Khalil, Ia, Khan, Ea, Khan, Mn, Khan, Ma, Khanal, Mn, Khang, Yh, Khater, Mm, Khoja, Ata, Kibret, Gd, Kiirithio, Dn, Kim, Yj, Kimokoti, Rw, Kopec, Ja, Koul, Pa, Krohn, Kj, Kumar, Ga, Kyu, Hh, Lad, Dp, Lal, Dk, Lang, Jj, Lansingh, Vc, Lazarus, Jv, Leasher, Jl, Lee, Ph, Leshargie, Ct, Liben, Ml, Lim, Ll, Lopez, Ad, Lorch, Sa, Lotufo, Pa, Lucas, Tcd, Lyons, Ra, Macarayan, Erk, Mackay, Mt, Maddison, Er, Malta, Dc, Mamun, Aa, Mansournia, Ma, Mantovani, Lg, Mapoma, Cc, Martins, Sco, Martins-Melo, Fr, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mcgrath, Jj, Mehta, Km, Meles, Kg, Memish, Za, Mengiste, Da, Mengistu, Dt, Menota, Bg, Mensah, Ga, Meretoja, Tj, Mezgebe, Hb, Miller, Tr, Mini, Gk, Mirrakhimov, Em, Mitchell, Pb, Mlashu, Fw, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Mola, Gl, Montañez Hernandez, Jc, Morrison, Sd, Mousavi, Sm, Mueller, Uo, Murthy, Gv, Musa, Ki, Naik, Ga, Nansseu, Jrn, Narayan, Kv, Nascimento, Br, Negoi, Ri, Newton, Cr, Ngunjiri, Jw, Nguyen, Th, Ningrum, Dna, Nong, Vm, Norheim, Of, Noubiap, Jjn, Obermeyer, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olagunju, To, Olivares, Pr, Oliveira, Ppv, Olsen, He, Olusanya, Bo, Olusanya, Jo, Opio, Jn, Ortega-Altamirano, Dv, Pain, Aw, Palone, Mrt, Pandian, Jd, Park, Ek, Patil, St, Patton, Gc, Paturi, Vr, Pedroso, Mm, Pedroza, Sp, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Piradov, Ma, Pond, Cd, Postma, Mj, Prasad, Nm, Quintana, Hk, Rahman, Ma, Rahman, Su, Rai, Rk, Raju, Sb, Rana, Sm, Rawaf, Dl, Ray, Se, Razo-García, Ca, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Ribeiro, Al, Rios Blancas, Mj, Rivera, Ja, Roth, Ga, Ruhago, Gm, Sabde, Yd, Sahraian, Ma, Saldanha, Rf, Salomon, Ja, Samy, Am, Sanabria, Jr, Sancheti, Pk, Sanchez-Niño, Md, Santric Milicevic, Mm, Sarker, Ar, Saylan, Mi, Schmidt, Mi, Schneider, Ijc, Schumacher, Ae, Schutte, Ae, Schwebel, Dc, Sepanlou, Sg, Servan-Mori, Ee, Shaikh, Ma, Shariful Islam, Sm, Shfare, Mt, Shrime, Mg, Shukla, Sr, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silveira, Dga, Singh, Ja, Singh, Np, Sinha, Dn, Sinke, Ah, Soares Filho, Am, Sobaih, Bha, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Stein, Dj, Stokes, Ma, Sufiyan, Mb, Suliankatchi, Ra, Sunguya, Bf, Sur, Pj, Sykes, Bl, Sylaja, Pn, Tadakamadla, Sk, Tadesse, Ah, Taffere, Gr, Tariku, At, Temsah, Mh, Tesema, Ag, Tesfaye, Dj, Thompson, Mj, To, Qg, Tran, Bx, Tran, Kb, Tripathy, Sp, Tuem, Kb, Ukwaja, Kn, Uthman, Oa, Uzochukwu, Bsc, Valdez, Pr, van Boven, Jfm, Vladimirov, Sk, Vlassov, Vv, Vollset, Se, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weaver, Mr, Weintraub, Rg, Weldegwergs, Kg, West, Te, White, Rg, Whiteford, Ha, Wolfe, Cd, Wondimkun, Ya, Wyper, Gma, Yan, Ll, Yimer, Nb, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaki, Me, Zaman, Sb, Zenebe, Zm, Zimsen, Srm, Zuhlke, Lj, Murray, Cjl, and Lozano, R.
Subjects: Peformance, Coverage, Dánartíðni, Lífslíkur, Life expectancy, GBD, Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best), universal health coverage, Article, access quality health care, health care access and quality index, Nations, Healthcare Acce, Cause-specific mortality, Psychology, Healthcare Access and Quality Index, Mælitæki, States, Medicine (all), Health care, Þjóðir, Public Health, Global Health, Social Medicine and Epidemiology, Quality, Heilbrigðisþjónusta, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Sálfræði, Indicator, Amenable mortality, Transition, we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8–98·1) in Iceland, followed by 96·6 (94·9–97·9) in Norway and 96·1 (94·5–97·3) in the Netherlands, to values as low as 18·6 (13·1–24·4) in the Central African Republic, 19·0 (14·3–23·7) in Somalia, and 23·4 (20·2–26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1–93·6) in Beijing to 48·0 (43·4–53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6–68·8) in Goa to 34·0 (30·3–38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view—and subsequent provision—of quality health care for all populations, Trends, Inequalities
Abstract: Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97.1 (95% UI 95.8-98.1) in Iceland, followed by 96.6 (94.9-97.9) in Norway and 96.1 (94.5-97.3) in the Netherlands, to values as low as 18.6 (13.1-24.4) in the Central African Republic, 19.0 (14.3-23.7) in Somalia, and 23.4 (20.2-26.8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91.5 (89.1-936) in Beijing to 48.0 (43.4-53.2) in Tibet (a 43.5-point difference), while India saw a 30.8-point disparity, from 64.8 (59.6-68.8) in Goa to 34.0 (30.3-38.1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4.8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20.9-point to 17.0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17.2-point to 20.4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view and subsequent provision of quality health care for all populations., Bill & Melinda Gates Foundation. Barbora de Courten is supported by a National Heart Foundation Future Leader Fellowship (100864). Ai Koyanagi’s work is supported by the Miguel Servet contract financed by the CP13/00150 and PI15/00862 projects, integrated into the National R + D + I and funded by the ISCIII —General Branch Evaluation and Promotion of Health Research—and the European Regional Development Fund (ERDF-FEDER). Alberto Ortiz was supported by Spanish Government (Instituto de Salud Carlos III RETIC REDINREN RD16/0019 FEDER funds). Ashish Awasthi acknowledges funding support from Department of Science and Technology, Government of India through INSPIRE Faculty scheme Boris Bikbov has received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 703226. Boris Bikbov acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Panniyammakal Jeemon acknowledges support from the clinical and public health intermediate fellowship from the Wellcome Trust and Department of Biotechnology, India Alliance (2015–20). Job F M van Boven was supported by the Department of Clinical Pharmacy & Pharmacology of the University Medical Center Groningen, University of Groningen, Netherlands. Olanrewaju Oladimeji is an African Research Fellow hosted by Human Sciences Research Council (HSRC), South Africa and he also has honorary affiliations with Walter Sisulu University (WSU), Eastern Cape, South Africa and School of Public Health, University of Namibia (UNAM), Namibia. He is indeed grateful for support from HSRC, WSU and UNAM. EUI is supported in part by the South African National Research Foundation (NRF UID: 86003). Ulrich Mueller acknowledges funding by the German National Cohort Study grant No 01ER1511/D, Gabrielle B Britton is supported by Secretaría Nacional de Ciencia, Tecnología e Innovación and Sistema Nacional de Investigación de Panamá. Giuseppe Remuzzi acknowledges that the work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Behzad Heibati would like to acknowledge Air pollution Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran. Syed Aljunid acknowledges the National University of Malaysia for providing the approval to participate in this GBD Project. Azeem Majeed and Imperial College London are grateful for support from the Northwest London National Insititute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research & Care. Tambe Ayuk acknowledges the Institute of Medical Research and Medicinal Plant Studies for office space provided. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). João Fernandes gratefully acknowledges funding from FCT–Fundação para a Ciência e a Tecnologia (grant number UID/Multi/50016/2013). Jan-Walter De Neve was supported by the Alexander von Humboldt Foundation. Kebede Deribe is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (201900). Kazem Rahimi was supported by grants from the Oxford Martin School, the NIHR Oxford BRC and the RCUK Global Challenges Research Fund. Laith J Abu-Raddad acknowledges the support of Qatar National Research Fund (NPRP 9-040-3-008) who provided the main funding for generating the data provided to the GBD-IHME effort. Liesl Zuhlke is funded by the national research foundation of South Africa and the Medical Research Council of South Africa. Monica Cortinovis acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Chuanhua Yu acknowleges support from the National Natural Science Foundation of China (grant number 81773552 and grant number 81273179) Norberto Perico acknowledges that work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Charles Shey Wiysonge’s work is supported by the South African Medical Research Council and the National Research Foundation of South Africa (grant numbers 106035 and 108571). John J McGrath is supported by grant APP1056929 from the John Cade Fellowship from the National Health and Medical Research Council and the Danish National Research Foundation (Niels Bohr Professorship). Quique Bassat is an ICREA (Catalan Institution for Research and Advanced Studies) research professor at ISGlobal. Richard G White is funded by the UK MRC and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement that is also part of the EDCTP2 programme supported by the European Union (MR/P002404/1), the Bill & Melinda Gates Foundation (TB Modelling and Analysis Consortium: OPP1084276/OPP1135288, CORTIS: OPP1137034/OPP1151915, Vaccines: OPP1160830), and UNITAID (4214-LSHTM-Sept15; PO 8477-0-600). Rafael Tabarés-Seisdedos was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. Mihajlo Jakovljevic acknowleges contribution from the Serbian Ministry of Education Science and Technological Development of the Republic of Serbia (grant OI 175 014). Shariful Islam is funded by a Senior Fellowship from Institute for Physical Activity and Nutrition, Deakin University and received career transition grants from High Blood Pressure Research Council of Australia. Sonia Saxena is funded by various grants from the NIHR. Stefanos Tyrovolas was supported by the Foundation for Education and European Culture, the Sara Borrell postdoctoral program (reference number CD15/00019 from the Instituto de Salud Carlos III (ISCIII–Spain) and the Fondos Europeo de Desarrollo Regional. Stefanos was awarded with a 6 months visiting fellowship funding at IHME from M-AES (reference no. MV16/00035 from the Instituto de Salud Carlos III). S Vittal Katikreddi was funded by a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the MRC (MC_UU_12017/13 & MC_ UU_12017/15) and the Scottish Government Chief Scientist Office (SPHSU13 & SPHSU15). Traolach S Brugha has received funding from NHS Digital UK to collect data used in this study. The work of Hamid Badali was financially supported by Mazandaran University of Medical Sciences, Sari, Iran. The work of Stefan Lorkowski is funded by the German Federal Ministry of Education and Research (nutriCARD, Grant agreement number 01EA1411A). Mariam Molokhia’s research was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We also thank the countless individuals who have contributed to GBD 2016 in various capacities.
Published: 2018

13. Stacking based ensemble learning framework for identification of nitrotyrosine sites.

Author: Parvez A, Ali SD, Tayara H, and Chong KT
Abstract: Protein nitrotyrosine is an essential post-translational modification that results from the nitration of tyrosine amino acid residues. This modification is known to be associated with the regulation and characterization of several biological functions and diseases. Therefore, accurate identification of nitrotyrosine sites plays a significant role in the elucidating progress of associated biological signs. In this regard, we reported an accurate computational tool known as iNTyro-Stack for the identification of protein nitrotyrosine sites. iNTyro-Stack is a machine-learning model based on a stacking algorithm. The base classifiers in stacking are selected based on the highest performance. The feature map employed is a linear combination of the amino composition encoding schemes, including the composition of k-spaced amino acid pairs and tri-peptide composition. The recursive feature elimination technique is used for significant feature selection. The performance of the proposed method is evaluated using k-fold cross-validation and independent testing approaches. iNTyro-Stack achieved an accuracy of 86.3% and a Matthews correlation coefficient (MCC) of 72.6% in cross-validation. Its generalization capability was further validated on an imbalanced independent test set, where it attained an accuracy of 69.32%. iNTyro-Stack outperforms existing state-of-the-art methods across both evaluation techniques. The github repository is create to reproduce the method and results of iNTyro-Stack, accessible on: https://github.com/waleed551/iNTyro-Stack/., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest related to this research., (Copyright © 2024 Elsevier Ltd. All rights reserved.)
Published: 2024
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14. Anaemia among adolescent girls, pregnant and lactating women in the southern rural region of Bangladesh: Prevalence and risk factors.

Author: Ara G, Hassan R, Haque MA, Boitchi AB, Ali SD, Kabir KS, Mahmud RI, Islam KA, Rahman H, and Islam Z
Subjects: Humans, Female, Bangladesh epidemiology, Adolescent, Pregnancy, Risk Factors, Prevalence, Young Adult, Cross-Sectional Studies, Adult, Anemia epidemiology, Lactation, Rural Population statistics & numerical data
Abstract: Anaemia is a major public health concern in developing countries, particularly among children, adolescents, and women of reproductive age. The study aimed to assess the anaemia status among adolescent girls, pregnant, and lactating women with their contributing factors in the southern rural regions of Bangladesh. This cross-sectional study was conducted among 400 adolescent girls, 375 pregnant, and 375 lactating women using a multistage cluster-random sampling technique. Anaemia was measured through haemoglobin concentration in blood capillaries collected with a Hemocue 301 machine. Multinomial logistic regression was used to determine the factors associated with anaemia. The average age of pregnant and lactating women was 24 years and 15.2 years for girls. Overall, the prevalence of anaemia was 50% among pregnant women, 46% among lactating women, and 38% among adolescent girls. The risk of anaemia among adolescent girls was higher among non-Muslim (aOR = 2.13, 95%CI:1.05-4.31), belonged to families having >5 members (aOR = 2.24, 95%CI:1.16-4.31) while exposure to media reduced their risk (aOR = 0.33, 95%CI:0.15-0.74). Pregnant women who consumed a diversified diet, washed their hands after toilet, and received ≥4 ANC visits had a lower likelihood of developing anaemia. Lactating women who were employed, consumed a diversified diet, washed their hands before preparing food, and after toilet, had been exposed to media, received ≥4 ANC visits, and consumed ≥90 IFA, had a lower risk of developing anaemia. However, anaemia was more likely to be associated with lactating women who were non-Muslim (aOR = 3.75; 95%CI:1.26-11.22). The high prevalence of anaemia emphasizes the need to reconsider the existing strategy for the prevention and control of micronutrient deficiencies in Bangladesh., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Ara et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Published: 2024
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15. Utilization of Synthetic Near-Infrared Spectra via Generative Adversarial Network to Improve Wood Stiffness Prediction.

Author: Ali SD, Raut S, Dahlen J, Schimleck L, Bergman R, Zhang Z, and Nasir V
Subjects: Elastic Modulus, Light, Machine Learning, Wood, Data Analysis
Abstract: Near-infrared (NIR) spectroscopy is widely used as a nondestructive evaluation (NDE) tool for predicting wood properties. When deploying NIR models, one faces challenges in ensuring representative training data, which large datasets can mitigate but often at a significant cost. Machine learning and deep learning NIR models are at an even greater disadvantage because they typically require higher sample sizes for training. In this study, NIR spectra were collected to predict the modulus of elasticity (MOE) of southern pine lumber (training set = 573 samples, testing set = 145 samples). To account for the limited size of the training data, this study employed a generative adversarial network (GAN) to generate synthetic NIR spectra. The training dataset was fed into a GAN to generate 313, 573, and 1000 synthetic spectra. The original and enhanced datasets were used to train artificial neural networks (ANNs), convolutional neural networks (CNNs), and light gradient boosting machines (LGBMs) for MOE prediction. Overall, results showed that data augmentation using GAN improved the coefficient of determination (R 2 ) by up to 7.02% and reduced the error of predictions by up to 4.29%. ANNs and CNNs benefited more from synthetic spectra than LGBMs, which only yielded slight improvement. All models showed optimal performance when 313 synthetic spectra were added to the original training data; further additions did not improve model performance because the quality of the datapoints generated by GAN beyond a certain threshold is poor, and one of the main reasons for this can be the size of the initial training data fed into the GAN. LGBMs showed superior performances than ANNs and CNNs on both the original and enhanced training datasets, which highlights the significance of selecting an appropriate machine learning or deep learning model for NIR spectral-data analysis. The results highlighted the positive impact of GAN on the predictive performance of models utilizing NIR spectroscopy as an NDE technique and monitoring tool for wood mechanical-property evaluation. Further studies should investigate the impact of the initial size of training data, the optimal number of generated synthetic spectra, and machine learning or deep learning models that could benefit more from data augmentation using GANs.
Published: 2024
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16. Factors affecting the micronutrient status of adolescent girls living in complex agro-aquatic ecological zones of Bangladesh.

Author: Ara G, Little DC, Mamun AA, de Roos B, Grieve E, Khanam M, Hasan SMT, Ireen S, Ali SD, Boitchi AB, Dijkhuizen MA, Ahmed T, and Roos N
Subjects: Female, Humans, Adolescent, Micronutrients, Bangladesh epidemiology, Cross-Sectional Studies, Vitamins, Prevalence, Nutritional Status, Trace Elements, Malnutrition, Iron Deficiencies
Abstract: Inadequate intake of both macro and micronutrients is the major determinant of micronutrient deficiencies in adolescent girls. This study assessed multiple micronutrient status including vitamin D, iron, vitamin A, and urinary iodine concentration among adolescent girls through two seasonal cross-sectional surveys conducted during dry and wet seasons. Mixed-effects linear and logistic regression analysis were conducted to assess associations between micronutrient status, salinity and seasonality. The mean age of the girls was 14 years. Vitamin (OH)D insufficiency was significantly higher in freshwater areas in wet season compared to dry season (wet season: 58% and dry season: 30%, P < 0.001). In wet season, risk of vitamin (OH)D insufficiency was three times higher compared to dry season (AOR: 3.03, 95% CI 1.71, 5.37, P < 0.001). The odds of vitamin (OH)D insufficiency was 11 times higher in fresh water areas compared to high saline areas (AOR: 11.51, 95% CI 3.40, 38.93, P < 0.001). The girls had higher risk of iron deficiency in wet season. Despite the environment being enriched with micronutrient-contained aquatic food, adolescent girls in coastal areas experience different micronutrient deficiencies. The high prevalence of vitamin (OH)D insufficiency in freshwater locations and seasonal iron deficiency in high saline areas needs attention., (© 2023. The Author(s).)
Published: 2023
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17. Interpretable machine learning identification of arginine methylation sites.

Author: Ali SD, Tayara H, and Chong KT
Subjects: Algorithms, Computational Biology, Machine Learning, Methylation, Proteins chemistry, Arginine chemistry, Arginine metabolism, Lysine chemistry, Lysine metabolism
Abstract: Protein methylation is one of the most prominent posttranslation modifications that essentially regulates several biological processes in eukaryotes. Therefore, identification of the arginine methylation site is crucial in deciphering its characteristics and functions in cell biology, disease mechanisms, and guided drug development. The computation methods address the long-term bottleneck together with the cost, time, and labor required in experimental methods for large-scale identification of protein arginine methylation sites. In this study, we proposed a robust machine learning-based computational tool known as iIRMethyl, employing the primary sequence and physicochemical properties of protein along with a two-step feature selection method for optimal selection of feature descriptors. Moreover, the performance of iIRMethyl was comprehensively evaluated via k-fold cross-validation on a benchmark dataset and independent test dataset. iIRMethyl demonstrated a remarkably greater performance than the state-of-the-art method and achieved an average area under the curve value of 0.99 for both k-fold cross-validation and an independent test set in the identification of protein arginine methylation sites. Furthermore, the outcomes reveal that iIRMethyl is a robust and accurate computational tool for large-scale identification of arginine methylation sites and would facilitate the understanding of their functional mechanisms and accelerating their application in drug development and clinical therapy. Additionally, the prediction mechanism of the proposed model iIRMethyl is interpreted using the SHapley Additive exPlanation algorithm., (Copyright © 2022 Elsevier Ltd. All rights reserved.)
Published: 2022
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18. Identification of Functional piRNAs Using a Convolutional Neural Network.

Author: Ali SD, Alam W, Tayara H, and Chong KT
Subjects: DNA Transposable Elements, Humans, RNA, Messenger genetics, RNA, Small Interfering genetics, Neoplasms genetics, Neural Networks, Computer
Abstract: Piwi-interacting RNAs (piRNAs) are a distinct sub-class of small non-coding RNAs that are mainly responsible for germline stem cell maintenance, gene stability, and maintaining genome integrity by repression of transposable elements. piRNAs are also expressed aberrantly and associated with various kinds of cancers. To identify piRNAs and their role in guiding target mRNA deadenylation, the currently available computational methods require urgent improvements in performance. To facilitate this, we propose a robust predictor based on a lightweight and simplified deep learning architecture using a convolutional neural network (CNN) to extract significant features from raw RNA sequences without the need for more customized features. The proposed model's performance is comprehensively evaluated using k-fold cross-validation on a benchmark dataset. The proposed model significantly outperforms existing computational methods in the prediction of piRNAs and their role in target mRNA deadenylation. In addition, a user-friendly and publicly-accessible web server is available at http://nsclbio.jbnu.ac.kr/tools/2S-piRCNN/.
Published: 2022
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19. Identification of piRNA disease associations using deep learning.

Author: Ali SD, Tayara H, and Chong KT
Abstract: Piwi-interacting RNAs (piRNAs) play a pivotal role in maintaining genome integrity by repression of transposable elements, gene stability, and association with various disease progressions. Cost-efficient computational methods for the identification of piRNA disease associations promote the efficacy of disease-specific drug development. In this regard, we developed a simple, robust, and efficient deep learning method for identifying the piRNA disease associations known as piRDA. The proposed architecture extracts the most significant and abstract information from raw sequences represented in a simplicated piRNA disease pair without any involvement of features engineering. Two-step positive unlabeled learning and bootstrapping technique are utilized to abstain from the false-negative and biased predictions dealing with positive unlabeled data. The performance of proposed method piRDA is evaluated using k-fold cross-validation. The piRDA is significantly improved in all the performance evaluation measures for the identification of piRNA disease associations in comparison to state-of-the-art method. Moreover, it is thus projected conclusively that the proposed computational method could play a significant role as a supportive and practical tool for primitive disease mechanisms and pharmaceutical research such as in academia and drug design. Eventually, the proposed model can be accessed using publicly available and user-friendly web tool athttp://nsclbio.jbnu.ac.kr/tools/piRDA/., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.)
Published: 2022
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20. The Burden of Mental Disorders in the Eastern Mediterranean Region, 1990-2013.

Author: Charara R, Forouzanfar M, Naghavi M, Moradi-Lakeh M, Afshin A, Vos T, Daoud F, Wang H, El Bcheraoui C, Khalil I, Hamadeh RR, Khosravi A, Rahimi-Movaghar V, Khader Y, Al-Hamad N, Makhlouf Obermeyer C, Rafay A, Asghar R, Rana SM, Shaheen A, Abu-Rmeileh NM, Husseini A, Abu-Raddad LJ, Khoja T, Al Rayess ZA, AlBuhairan FS, Hsairi M, Alomari MA, Ali R, Roshandel G, Terkawi AS, Hamidi S, Refaat AH, Westerman R, Kiadaliri AA, Akanda AS, Ali SD, Bacha U, Badawi A, Bazargan-Hejazi S, Faghmous IA, Fereshtehnejad SM, Fischer F, Jonas JB, Kuate Defo B, Mehari A, Omer SB, Pourmalek F, Uthman OA, Mokdad AA, Maalouf FT, Abd-Allah F, Akseer N, Arya D, Borschmann R, Brazinova A, Brugha TS, Catalá-López F, Degenhardt L, Ferrari A, Haro JM, Horino M, Hornberger JC, Huang H, Kieling C, Kim D, Kim Y, Knudsen AK, Mitchell PB, Patton G, Sagar R, Satpathy M, Savuon K, Seedat S, Shiue I, Skogen JC, Stein DJ, Tabb KM, Whiteford HA, Yip P, Yonemoto N, Murray CJ, and Mokdad AH
Subjects: Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Child, Child, Preschool, Female, Humans, Infant, Infant, Newborn, Life Expectancy, Male, Mediterranean Region epidemiology, Middle Aged, Sex Factors, Time Factors, Young Adult, Global Health, Health Status, Mental Disorders epidemiology
Abstract: The Eastern Mediterranean Region (EMR) is witnessing an increase in chronic disorders, including mental illness. With ongoing unrest, this is expected to rise. This is the first study to quantify the burden of mental disorders in the EMR. We used data from the Global Burden of Disease study (GBD) 2013. DALYs (disability-adjusted life years) allow assessment of both premature mortality (years of life lost-YLLs) and nonfatal outcomes (years lived with disability-YLDs). DALYs are computed by adding YLLs and YLDs for each age-sex-country group. In 2013, mental disorders contributed to 5.6% of the total disease burden in the EMR (1894 DALYS/100,000 population): 2519 DALYS/100,000 (2590/100,000 males, 2426/100,000 females) in high-income countries, 1884 DALYS/100,000 (1618/100,000 males, 2157/100,000 females) in middle-income countries, 1607 DALYS/100,000 (1500/100,000 males, 1717/100,000 females) in low-income countries. Females had a greater proportion of burden due to mental disorders than did males of equivalent ages, except for those under 15 years of age. The highest proportion of DALYs occurred in the 25-49 age group, with a peak in the 35-39 years age group (5344 DALYs/100,000). The burden of mental disorders in EMR increased from 1726 DALYs/100,000 in 1990 to 1912 DALYs/100,000 in 2013 (10.8% increase). Within the mental disorders group in EMR, depressive disorders accounted for most DALYs, followed by anxiety disorders. Among EMR countries, Palestine had the largest burden of mental disorders. Nearly all EMR countries had a higher mental disorder burden compared to the global level. Our findings call for EMR ministries of health to increase provision of mental health services and to address the stigma of mental illness. Moreover, our results showing the accelerating burden of mental health are alarming as the region is seeing an increased level of instability. Indeed, mental health problems, if not properly addressed, will lead to an increased burden of diseases in the region., Competing Interests: We would like to declare the following commercial affiliations: Dr. Anwar Rafay is employed by Contech International health consultants. Syed Danish Ali is employed by SIR Consultants. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Published: 2017
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21. Health in times of uncertainty in the eastern Mediterranean region, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Author: Mokdad AH, Forouzanfar MH, Daoud F, El Bcheraoui C, Moradi-Lakeh M, Khalil I, Afshin A, Tuffaha M, Charara R, Barber RM, Wagner J, Cercy K, Kravitz H, Coates MM, Robinson M, Estep K, Steiner C, Jaber S, Mokdad AA, O'Rourke KF, Chew A, Kim P, El Razek MM, Abdalla S, Abd-Allah F, Abraham JP, Abu-Raddad LJ, Abu-Rmeileh NM, Al-Nehmi AA, Akanda AS, Al Ahmadi H, Al Khabouri MJ, Al Lami FH, Al Rayess ZA, Alasfoor D, AlBuhairan FS, Aldhahri SF, Alghnam S, Alhabib S, Al-Hamad N, Ali R, Ali SD, Alkhateeb M, AlMazroa MA, Alomari MA, Al-Raddadi R, Alsharif U, Al-Sheyab N, Alsowaidi S, Al-Thani M, Altirkawi KA, Amare AT, Amini H, Ammar W, Anwari P, Asayesh H, Asghar R, Assabri AM, Assadi R, Bacha U, Badawi A, Bakfalouni T, Basulaiman MO, Bazargan-Hejazi S, Bedi N, Bhakta AR, Bhutta ZA, Bin Abdulhak AA, Boufous S, Bourne RR, Danawi H, Das J, Deribew A, Ding EL, Durrani AM, Elshrek Y, Ibrahim ME, Eshrati B, Esteghamati A, Faghmous IA, Farzadfar F, Feigl AB, Fereshtehnejad SM, Filip I, Fischer F, Gankpé FG, Ginawi I, Gishu MD, Gupta R, Habash RM, Hafezi-Nejad N, Hamadeh RR, Hamdouni H, Hamidi S, Harb HL, Hassanvand MS, Hedayati MT, Heydarpour P, Hsairi M, Husseini A, Jahanmehr N, Jha V, Jonas JB, Karam NE, Kasaeian A, Kassa NA, Kaul A, Khader Y, Khalifa SE, Khan EA, Khan G, Khoja T, Khosravi A, Kinfu Y, Defo BK, Balaji AL, Lunevicius R, Obermeyer CM, Malekzadeh R, Mansourian M, Marcenes W, Farid HM, Mehari A, Mehio-Sibai A, Memish ZA, Mensah GA, Mohammad KA, Nahas Z, Nasher JT, Nawaz H, Nejjari C, Nisar MI, Omer SB, Parsaeian M, Peprah EK, Pervaiz A, Pourmalek F, Qato DM, Qorbani M, Radfar A, Rafay A, Rahimi K, Rahimi-Movaghar V, Rahman SU, Rai RK, Rana SM, Rao SR, Refaat AH, Resnikoff S, Roshandel G, Saade G, Saeedi MY, Sahraian MA, Saleh S, Sanchez-Riera L, Satpathy M, Sepanlou SG, Setegn T, Shaheen A, Shahraz S, Sheikhbahaei S, Shishani K, Sliwa K, Tavakkoli M, Terkawi AS, Uthman OA, Westerman R, Younis MZ, El Sayed Zaki M, Zannad F, Roth GA, Wang H, Naghavi M, Vos T, Al Rabeeah AA, Lopez AD, and Murray CJ
Subjects: Adult, Africa epidemiology, Aged, Aged, 80 and over, Aging, Child, Child, Preschool, Diarrhea epidemiology, Humans, Infant, Infant, Newborn, Life Expectancy, Middle Aged, Middle East epidemiology, Noncommunicable Diseases epidemiology, Obesity complications, Risk Factors, Cardiovascular Diseases epidemiology, Global Burden of Disease trends, Infections epidemiology, Obesity epidemiology, Quality-Adjusted Life Years, Social Problems, Wounds and Injuries epidemiology
Abstract: Background: The eastern Mediterranean region is comprised of 22 countries: Afghanistan, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pakistan, Palestine, Qatar, Saudi Arabia, Somalia, Sudan, Syria, Tunisia, the United Arab Emirates, and Yemen. Since our Global Burden of Disease Study 2010 (GBD 2010), the region has faced unrest as a result of revolutions, wars, and the so-called Arab uprisings. The objective of this study was to present the burden of diseases, injuries, and risk factors in the eastern Mediterranean region as of 2013., Methods: GBD 2013 includes an annual assessment covering 188 countries from 1990 to 2013. The study covers 306 diseases and injuries, 1233 sequelae, and 79 risk factors. Our GBD 2013 analyses included the addition of new data through updated systematic reviews and through the contribution of unpublished data sources from collaborators, an updated version of modelling software, and several improvements in our methods. In this systematic analysis, we use data from GBD 2013 to analyse the burden of disease and injuries in the eastern Mediterranean region specifically., Findings: The leading cause of death in the region in 2013 was ischaemic heart disease (90·3 deaths per 100 000 people), which increased by 17·2% since 1990. However, diarrhoeal diseases were the leading cause of death in Somalia (186·7 deaths per 100 000 people) in 2013, which decreased by 26·9% since 1990. The leading cause of disability-adjusted life-years (DALYs) was ischaemic heart disease for males and lower respiratory infection for females. High blood pressure was the leading risk factor for DALYs in 2013, with an increase of 83·3% since 1990. Risk factors for DALYs varied by country. In low-income countries, childhood wasting was the leading cause of DALYs in Afghanistan, Somalia, and Yemen, whereas unsafe sex was the leading cause in Djibouti. Non-communicable risk factors were the leading cause of DALYs in high-income and middle-income countries in the region. DALY risk factors varied by age, with child and maternal malnutrition affecting the younger age groups (aged 28 days to 4 years), whereas high bodyweight and systolic blood pressure affected older people (aged 60-80 years). The proportion of DALYs attributed to high body-mass index increased from 3·7% to 7·5% between 1990 and 2013. Burden of mental health problems and drug use increased. Most increases in DALYs, especially from non-communicable diseases, were due to population growth. The crises in Egypt, Yemen, Libya, and Syria have resulted in a reduction in life expectancy; life expectancy in Syria would have been 5 years higher than that recorded for females and 6 years higher for males had the crisis not occurred., Interpretation: Our study shows that the eastern Mediterranean region is going through a crucial health phase. The Arab uprisings and the wars that followed, coupled with ageing and population growth, will have a major impact on the region's health and resources. The region has historically seen improvements in life expectancy and other health indicators, even under stress. However, the current situation will cause deteriorating health conditions for many countries and for many years and will have an impact on the region and the rest of the world. Based on our findings, we call for increased investment in health in the region in addition to reducing the conflicts., Funding: Bill & Melinda Gates Foundation., (Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.)
Published: 2016
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22. Vitamin D deficiency and possible link with Bony pain and onset of Osteoporosis.

Author: Shah SK, Taufiq I, Najjad MK, Ali SD, and Siddiqui MA
Abstract: Objective: To explore if vitamin D deficiency had a direct correlation with bone pain or if it contributes in any way to the onset of osteoporosis., Methods: The cross sectional Study was conducted from February to May 2014, presented at Liaquat National Hospital, Karachi, and comprised Orthopaedic outpatients. Who were questioned, examined and counselled, before a questionnaire was filled that included questions about their complaint, and its severity. Several blood test reports were incorporated including serum Vitamin D, to evaluate kidney and liver functions. Dual energy X-ray absorptiometry scans of the lumber and hip regions were also included. Data was collected manually and analysed using SPSS version 16., Results: The mean age of the 65 subjects, was 52.±16 SD years, and 54(83.1%) were overweight with body mass index of 29.7kg/m2. Besides, 61(93.8%) had a positive association of low vitamin D levels as a causative agent for bone pain with mean pain severity index 6±1 SD. On the other hand 25(38.5%) were diagnosed as cases of osteoporosis, and, of them, 21(84%) had low vitamin D levels., Conclusions: Deficiency of vitamin D was directly related to the intensity of bone pain. Some patients had vitamin D deficiency along with osteoporosis, which may have aggravating effect in this context.
Published: 2014

23. Functional outcome of ACL reconstruction using patellar bone tendon bone graft.

Author: Ali SD, Noor S, Shah SD, Mangi IK, Ali Shah SK, and Sufyan M
Abstract: Purpose: To evaluate the mid-term functional outcome using Lysholm score of anterior cruciate ligamentreconstruction using bone patella-tendon bone graft., Methods: The retrospective study of prospectively collected data was conducted at Liaquat National Hospital, Karachi, from June 2010to June 2013, and comprised patients with complete anterior cruciate ligamenttear who were treated with diagnostic arthroscopy and open reconstruction using bone patella-tendon bone graft. All patients were operated under tourniquet control and knee immobiliser was applied. Straight leg raise procedure was started on 2nd postoperative day. One year after surgery, functional outcome was assessed using Lysholm score., Results: All the 36(100%) patients in the study were males. Four (11%) patients were lost to follow-up and were excluded, while 32(89%) completed the study. Right knee was involved in 16(50%) patients while left knee was involved in 16(50%) patients. Overall, 31(97%) patients had history of contact sports injury. The average age of patients was 28.25±8.32 years. All patients were operated at an average of 17.5±10.3 weeks. The ligament tear was associated with medial meniscal tear in 16(50%) patients, while lateral meniscal tear was noted in 10(31.25%). The mean Lysholm score was 83.06±4.17at 1 year (fair to good outcome). The average range of motion 1 year after surgery was 127.5±11.25. Loss of extension <3o was noted in 20(62.5%) patients, while >3o was noted in 12(37.5%). The average loss of extension was 3.5±2.3 degrees. Two (6.25%) patients developed superficial infection which subsided with oral antibiotics. Anterior knee pain was reported by 8(25%) patients., Conclusions: Patellar bone tendon bone graft was a reliable method for reconstruction of anterior cruciate ligament.
Published: 2014

24. Precontoured anatomical plates new era in the complex tibail plateau fractures fixation.

Author: Mangi IK, Taufiq I, Shah SD, Shah SA, and Rahim Najjad MK
Abstract: Objective: Functional outcome of Intraarticular Tibial Plateau Fractures fixed with precontoured anatomical plates using Knee Society Score., Methods: Observational study with retrospective review of collected data. Patient's demography, mechanism of injury, schatzker's classification includingtype IV, V and VI. All patients underwent screw and plate fixation using two incision technique with pre-contoured anatomical plates and intercondylar lag screws where indicated. Passive range of motion exercises started at 2 weeks. Postoperative knee pain, range of motion and stiffness were recorded at followup 3 and 4 months. Mean±SD were calculated for quantitative variables and qualitative variables were presented with frequency and percentages. The association of outcome (Knee Society Score) with gender, age and Schatzker's type was evaluated by applying Fisher's Exact test considering p-value <0.05 as significant., Results: Twenty-five patients were included in study. 20 patients were available and 05 lost to follow up. 16 were males and 4 females out of 20 patients. Average age is 36.2±12.89 years. All patients sustained injuries after RTA. 5 patients had postoperative knee pain while remaining were pain free. Average flexion was 123.8 with (SD 8.88)range of 105 to 135 degree. Average extension was 3.15 with (SD 2.41) range of 0 to 8 degress. 4 patients developed stiffness of knee. 2 patients symptomatic implant. All fractures healed at follow up at 4 months. According to Knee Society score (SD 7.65) 14 cases scored as good, 4 cases scored fair and 2 cases scored poor. There was no association of knee score was found with gender (p=0.493) but significant association of knee score was found with age (p=0.007) and Schatzker's type (p=0.028)., Conclusions: Tibial plateau fractures can be effectively treated by anatomical reduction and absolute fixation using pre-contoured anatomical plates. Functional outcome calculated by Knee Society score is better in young patients. With appropriate surgical techniques and early post-operative rehabilitation, good functional results can be achieved.
Published: 2014

25. Common presentation uncommon diagnosis primary omental torsion.

Author: Ali SD and Sheeraz-ur-Rahman S
Subjects: Abdomen, Acute diagnosis, Abdomen, Acute therapy, Adult, Humans, Male, Peritoneal Diseases therapy, Torsion Abnormality therapy, Young Adult, Abdomen, Acute etiology, Omentum, Peritoneal Diseases complications, Peritoneal Diseases diagnosis, Torsion Abnormality complications, Torsion Abnormality diagnosis
Abstract: Primary omental torsion is a rare cause of acute abdomen and mimics common acute abdominal condition like appendicitis. Torsion of the greater omentum may be primary or secondary. Here we present 2 cases admitted through emergency with the pain in right iliac fossa with this unusual diagnosis.
Published: 2013

26. A brewing access crisis.

Author: Ali SD
Subjects: Female, Health Services Accessibility economics, Humans, Insurance, Health, Reimbursement, Liability, Legal, Malpractice legislation & jurisprudence, United States, Health Services Accessibility trends, Mammography economics
Published: 2003

27. Inhibition of camel lens zeta-crystallin/NADPH:quinone oxidoreductase activity by chloranilic acid.

Author: al-Hamidi AA, Riskuwa AS, and Ali SD
Subjects: Animals, Camelus, Chloranil pharmacology, Kinetics, Benzoquinones pharmacology, Crystallins antagonists & inhibitors, NAD(P)H Dehydrogenase (Quinone) antagonists & inhibitors
Abstract: Camel lens zeta-crystallin/NADPH:quinone oxidoreductase activity was inhibited by chloranilic acid (2,5-dichloro-3,6-dihydroxy-1,4-benzoquinone) with NADPH as an electron donor and 9,10-phenanthrenequinone (PQ) as an electron acceptor in a time-independent but concentration dependent manner. The IC50 of chloranilic acid was 1 microM. The inhibition was noncompetitive with respect to both NADPH and PQ as deduced by Lineweaver-Burk plots. The estimated inhibition constant (Ki) was 0.8 microM for both NADPH and PQ. Examination of other benzoquinones suggested that the presence of -OH and -Cl on benzoquinone was essential for the inhibition.
Published: 1997
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28. The partographs of the Jamaican parturient.

Author: Jayasinghe RG and Ali SD
Subjects: Female, Humans, Jamaica, Pregnancy, Cervix Uteri physiology, Labor, Obstetric
Published: 1977

29. Extra-nodal reticulum cell sarcoma of the terminal ileum with intussusception.

Author: Elechi EN, Ali SD, Calhoun T, and Kurtz LH
Subjects: Cecal Neoplasms pathology, Humans, Lymphoma, Non-Hodgkin pathology, Male, Middle Aged, Cecal Neoplasms complications, Intussusception complications, Lymphoma, Non-Hodgkin complications
Published: 1974

30. Hidradenitis suppurativa: review of the literature and management of the axillary lesion.

Author: Mustafa EB, Ali SD, and Kurtz LH
Subjects: Adult, Axilla, Humans, Inflammation surgery, Skin Transplantation, Suppuration, Transplantation, Autologous, Apocrine Glands surgery, Sweat Glands surgery
Abstract: Hidradenitis suppurativa is a suppurative inflammatory disease of the apocrine sweat glands. It affects the apocrine gland bearing regions, the axillae being the most common site. It causes considerable morbidity and has several complications. The etiology is unknown and there is no standard method of treatment. A comprehensive review of the literature is presented demonstrating a paucity of information about this disease. The authors' experience and the management of the axillary lesion is outlined. Radical excision of the apocrine gland bearing area with split thickness skin graft (STSG) after one week is the method of choice. A reinforced sling is used for arm immobilization after grafting. The predictability of this technique makes it the preferred method of treatment. Also, more effort is urged towards better understanding of this neglected but serious health problem.
Published: 1980

31. Gunshot wounds of the inferior vena cava: report of five survivors.

Author: Aderoju S, Ali SD, Calhoun T, and Kurtz LH
Subjects: Adolescent, Adult, Female, Humans, Male, Middle Aged, Vena Cava, Inferior surgery, Vena Cava, Inferior injuries, Wounds, Gunshot surgery
Published: 1976

32. The use of pneumoperitoneum in the treatment of megaherniae.

Author: Ali SD, Calhoun T, and Kurtz LH
Subjects: Aged, Hernia, Inguinal surgery, Humans, Male, Postoperative Complications, Preoperative Care, Prognosis, Urography, Hernia, Inguinal therapy, Pneumoperitoneum, Artificial methods
Published: 1975

33. Pancreatic ascites.

Author: Muna D, Ali SD, Jean-Jacques A, Calhoun T, and Kurtz LH
Subjects: Adult, Diagnosis, Differential, Female, Humans, Liver Cirrhosis diagnosis, Male, Pancreatitis diagnosis, Ascites complications, Pancreatic Cyst complications, Pancreatitis complications
Published: 1975

34. Acalculous cholecystitis and malignant ileal carcinoid tumor.

Author: Odelowo EO, Ali SD, Calhoun T, and Kurtz LH
Subjects: Aged, Drug Interactions, Humans, Male, Carcinoma, Squamous Cell diagnosis, Cholecystitis surgery, Ileum, Intestinal Neoplasms diagnosis
Published: 1975

35. Colostomy. Intraperitoneal or extraperitoneal closure?

Author: Adeyemo A, Gaillard WE Jr, Ali SD, Calhoun T, and Kurtz LH
Subjects: Colonic Diseases etiology, Colostomy adverse effects, Feces, Hematoma etiology, Humans, Intestinal Fistula etiology, Peritoneum, Surgical Wound Infection etiology, Sutures adverse effects, Colostomy methods
Abstract: Forty-three patients who underwent intraperitoneal closure of colostomy are reported on. Complication rates of 4.6 per cent for wound infection and 4.6 per cent for fecal fistulas appear significantly lower than the 10 to 21 per cent complication rates reported for colostomy closure using other technics.
Published: 1975
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36. Acute emphasematous cholecystitis. A case report and review of the literature.

Author: Howell HD, Dike NA, Ali SD, Calhoun T, and Kurtz LH
Subjects: Acute Disease, Alcoholism complications, Cholecystectomy, Cystic Duct, Humans, Male, Middle Aged, Radiography, Cholecystitis diagnostic imaging, Gangrene
Published: 1975

37. Acute colonic obstruction secondary to pancreatitis. A case report and review of the literature.

Author: Carter P, Ali SD, Calhoun T, and Kurtz LH
Subjects: Acute Disease, Adult, Barium Sulfate, Colonic Diseases diagnostic imaging, Colostomy, Humans, Intestinal Obstruction diagnostic imaging, Male, Radiography, Colonic Diseases etiology, Intestinal Obstruction etiology, Pancreatitis complications
Published: 1974

38. Management of external fistulas of the gastrointestinal tract.

Author: Ali SD and Leffall LD Jr
Subjects: Adult, Aged, Colonic Diseases diagnostic imaging, Colonic Diseases etiology, Colonic Diseases surgery, Female, Gastric Fistula diagnostic imaging, Gastric Fistula etiology, Gastric Fistula surgery, Humans, Intestinal Fistula diagnostic imaging, Intestinal Fistula etiology, Intestinal Fistula surgery, Male, Middle Aged, Parenteral Nutrition, Postoperative Complications, Radiography, Water-Electrolyte Balance, Colonic Diseases therapy, Gastric Fistula therapy, Ileum, Intestinal Fistula therapy, Jejunum
Published: 1972
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39. [Effect of vitamin B6 on blood lipids and cholesterinemia in clinical and experimental conditions].

Author: SHEIKH-ALI SD
Subjects: Humans, Cholesterol blood, Lipids blood, Vitamin B 6 pharmacology
Published: 1959

40. Carcinosarcoma of the esophagus. Case report and review of the literature.

Author: Calhoun T, Ali SD, Muna D, Kurtz LH, Simmons RL, and Nash EC
Subjects: Adult, Carcinosarcoma surgery, Esophageal Neoplasms surgery, Esophagoscopy, Humans, Male, Carcinosarcoma pathology, Esophageal Neoplasms pathology
Published: 1973

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