Centre des Sciences du Goût et de l'Alimentation

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,
\nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981,
\nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826,
\nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376,
\nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294,
\nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198,
\nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544,
\nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107,
\nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756,
\nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6,
\nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58,
\nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007,
\nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591,
\nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930,
\nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794,
\nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727,
\nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986,
\nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409,
\nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368,
\nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884,
\nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239,
\nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997,
\nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798,
\nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909,
\nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336,
\nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419,
\nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490,
\nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401,
\nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880,
\nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913,
\nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381,
\nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112,
\nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812,
\nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287,
\nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308,
\nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901,
\nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141,
\nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374,
\nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822,
\nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480,
\nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171,
\nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789,
\nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217,
\nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24,
\nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700,
\nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983,
\nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002,
\nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318,
\nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462,
\nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884,
\nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996,
\nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628,
\nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003,
\nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434,
\nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783,
\nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514,
\nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172,
\nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113,
\nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135,
\nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702,
\nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703,
\nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308,
\nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290,
\nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105,
\nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563,
\nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936,
\nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657,
\nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254,
\nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694,
\nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781,
\nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533,
\nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829,
\nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395,
\nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566,
\nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767,
\nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301,
\nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919,
\nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576,
\nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572,
\nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940,
\nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340,
\nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254,
\nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604,
\nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182,
\nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775,
\nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,

BACKGROUND: Contemporary data for causes of vision impairment and blindness form an important basis of recommendations in public health policies. Refreshment of the Global Vision Database with recently published data sources permitted modelling of cause of vision loss data from 1990 to 2015, further disaggregation by cause, and forecasts to 2020. METHODS: In this systematic review and meta-analysis, we analysed published and unpublished population-based data for the causes of vision impairment and blindness from 1980 to 2014. We identified population-based studies published before July 8, 2014, by searching online databases with no language restrictions (MEDLINE from Jan 1, 1946, and Embase from Jan 1, 1974, and the WHO Library Database). We fitted a series of regression models to estimate the proportion of moderate or severe vision impairment (defined as presenting visual acuity of <6/18 but ≥3/60 in the better eye) and blindness (presenting visual acuity of <3/60 in the better eye) by cause, age, region, and year. FINDINGS: We identified 288 studies of 3 983 541 participants contributing data from 98 countries. Among the global population with moderate or severe vision impairment in 2015 (216·6 million [80% uncertainty interval 98·5 million to 359·1 million]), the leading causes were uncorrected refractive error (116·3 million [49·4 million to 202·1 million]), cataract (52·6 million [18·2 million to 109·6 million]), age-related macular degeneration (8·4 million [0·9 million to 29·5 million]), glaucoma (4·0 million [0·6 million to 13·3 million]), and diabetic retinopathy (2·6 million [0·2 million to 9·9 million]). Among the global population who were blind in 2015 (36·0 million [12·9 million to 65·4 million]), the leading causes were cataract (12·6 million [3·4 million to 28·7 million]), uncorrected refractive error (7·4 million [2·4 million to 14·8 million]), and glaucoma (2·9 million [0·4 million to 9·9 million]). By 2020, among the global population with moderate or severe vision impairment (237·1 million [101·5 million to 399·0 million]), the number of people affected by uncorrected refractive error is anticipated to rise to 127·7 million (51·0 million to 225·3 million), by cataract to 57·1 million (17·9 million to 124·1 million), by age-related macular degeneration to 8·8 million (0·8 million to 32·1 million), by glaucoma to 4·5 million (0·5 million to 15·4 million), and by diabetic retinopathy to 3·2 million (0·2 million to 12·9 million). By 2020, among the global population who are blind (38·5 million [13·2 million to 70·9 million]), the number of patients blind because of cataract is anticipated to rise to 13·4 million (3·3 million to 31·6 million), because of uncorrected refractive error to 8·0 million (2·5 million to 16·3 million), and because of glaucoma to 3·2 million (0·4 million to 11·0 million). Cataract and uncorrected refractive error combined contributed to 55% of blindness and 77% of vision impairment in adults aged 50 years and older in 2015. World regions varied markedly in the causes of blindness and vision impairment in this age group, with a low prevalence of cataract (<22% for blindness and 14·1-15·9% for vision impairment) and a high prevalence of age-related macular degeneration (>14% of blindness) as causes in the high-income subregions. Blindness and vision impairment at all ages in 2015 due to diabetic retinopathy (odds ratio 2·52 [1·48-3·73]) and cataract (1·21 [1·17-1·25]) were more common among women than among men, whereas blindness and vision impairment due to glaucoma (0·71 [0·57-0·86]) and corneal opacity (0·54 [0·43-0·66]) were more common among men than among women, with no sex difference related to age-related macular degeneration (0·91 [0·70-1·14]). INTERPRETATION: The number of people affected by the common causes of vision loss has increased substantially as the population increases and ages. Preventable vision loss due to cataract (reversible with surgery) and refractive error (reversible with spectacle correction) continue to cause most cases of blindness and moderate or severe vision impairment in adults aged 50 years and older. A large scale-up of eye care provision to cope with the increasing numbers is needed to address avoidable vision loss. FUNDING: Brien Holden Vision Institute.

BACKGROUND: Many causes of vision impairment can be prevented or treated. With an ageing global population, the demands for eye health services are increasing. We estimated the prevalence and relative contribution of avoidable causes of blindness and vision impairment globally from 1990 to 2020. We aimed to compare the results with the World Health Assembly Global Action Plan (WHA GAP) target of a 25% global reduction from 2010 to 2019 in avoidable vision impairment, defined as cataract and undercorrected refractive error. METHODS: We did a systematic review and meta-analysis of population-based surveys of eye disease from January, 1980, to October, 2018. We fitted hierarchical models to estimate prevalence (with 95% uncertainty intervals [UIs]) of moderate and severe vision impairment (MSVI; presenting visual acuity from <6/18 to 3/60) and blindness (<3/60 or less than 10° visual field around central fixation) by cause, age, region, and year. Because of data sparsity at younger ages, our analysis focused on adults aged 50 years and older. FINDINGS: Global crude prevalence of avoidable vision impairment and blindness in adults aged 50 years and older did not change between 2010 and 2019 (percentage change -0·2% [95% UI -1·5 to 1·0]; 2019 prevalence 9·58 cases per 1000 people [95% IU 8·51 to 10·8], 2010 prevalence 96·0 cases per 1000 people [86·0 to 107·0]). Age-standardised prevalence of avoidable blindness decreased by -15·4% [-16·8 to -14·3], while avoidable MSVI showed no change (0·5% [-0·8 to 1·6]). However, the number of cases increased for both avoidable blindness (10·8% [8·9 to 12·4]) and MSVI (31·5% [30·0 to 33·1]). The leading global causes of blindness in those aged 50 years and older in 2020 were cataract (15·2 million cases [9% IU 12·7-18·0]), followed by glaucoma (3·6 million cases [2·8-4·4]), undercorrected refractive error (2·3 million cases [1·8-2·8]), age-related macular degeneration (1·8 million cases [1·3-2·4]), and diabetic retinopathy (0·86 million cases [0·59-1·23]). Leading causes of MSVI were undercorrected refractive error (86·1 million cases [74·2-101·0]) and cataract (78·8 million cases [67·2-91·4]). INTERPRETATION: Results suggest eye care services contributed to the observed reduction of age-standardised rates of avoidable blindness but not of MSVI, and that the target in an ageing global population was not reached. FUNDING: Brien Holden Vision Institute, Fondation Théa, The Fred Hollows Foundation, Bill & Melinda Gates Foundation, Lions Clubs International Foundation, Sightsavers International, and University of Heidelberg.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

BACKGROUND: Global and regional prevalence estimates for blindness and vision impairment are important for the development of public health policies. We aimed to provide global estimates, trends, and projections of global blindness and vision impairment. METHODS: We did a systematic review and meta-analysis of population-based datasets relevant to global vision impairment and blindness that were published between 1980 and 2015. We fitted hierarchical models to estimate the prevalence (by age, country, and sex), in 2015, of mild visual impairment (presenting visual acuity worse than 6/12 to 6/18 inclusive), moderate to severe visual impairment (presenting visual acuity worse than 6/18 to 3/60 inclusive), blindness (presenting visual acuity worse than 3/60), and functional presbyopia (defined as presenting near vision worse than N6 or N8 at 40 cm when best-corrected distance visual acuity was better than 6/12). FINDINGS: Globally, of the 7·33 billion people alive in 2015, an estimated 36·0 million (80% uncertainty interval [UI] 12·9-65·4) were blind (crude prevalence 0·48%; 80% UI 0·17-0·87; 56% female), 216·6 million (80% UI 98·5-359·1) people had moderate to severe visual impairment (2·95%, 80% UI 1·34-4·89; 55% female), and 188·5 million (80% UI 64·5-350·2) had mild visual impairment (2·57%, 80% UI 0·88-4·77; 54% female). Functional presbyopia affected an estimated 1094·7 million (80% UI 581·1-1686·5) people aged 35 years and older, with 666·7 million (80% UI 364·9-997·6) being aged 50 years or older. The estimated number of blind people increased by 17·6%, from 30·6 million (80% UI 9·9-57·3) in 1990 to 36·0 million (80% UI 12·9-65·4) in 2015. This change was attributable to three factors, namely an increase because of population growth (38·4%), population ageing after accounting for population growth (34·6%), and reduction in age-specific prevalence (-36·7%). The number of people with moderate and severe visual impairment also increased, from 159·9 million (80% UI 68·3-270·0) in 1990 to 216·6 million (80% UI 98·5-359·1) in 2015. INTERPRETATION: There is an ongoing reduction in the age-standardised prevalence of blindness and visual impairment, yet the growth and ageing of the world's population is causing a substantial increase in number of people affected. These observations, plus a very large contribution from uncorrected presbyopia, highlight the need to scale up vision impairment alleviation efforts at all levels. FUNDING: Brien Holden Vision Institute.

BACKGROUND: To contribute to the WHO initiative, VISION 2020: The Right to Sight, an assessment of global vision impairment in 2020 and temporal change is needed. We aimed to extensively update estimates of global vision loss burden, presenting estimates for 2020, temporal change over three decades between 1990-2020, and forecasts for 2050. METHODS: We did a systematic review and meta-analysis of population-based surveys of eye disease from January, 1980, to October, 2018. Only studies with samples representative of the population and with clearly defined visual acuity testing protocols were included. We fitted hierarchical models to estimate 2020 prevalence (with 95% uncertainty intervals [UIs]) of mild vision impairment (presenting visual acuity ≥6/18 and <6/12), moderate and severe vision impairment (<6/18 to 3/60), and blindness (<3/60 or less than 10° visual field around central fixation); and vision impairment from uncorrected presbyopia (presenting near vision <N6 or <N8 at 40 cm where best-corrected distance visual acuity is ≥6/12). We forecast estimates of vision loss up to 2050. FINDINGS: In 2020, an estimated 43·3 million (95% UI 37·6-48·4) people were blind, of whom 23·9 million (55%; 20·8-26·8) were estimated to be female. We estimated 295 million (267-325) people to have moderate and severe vision impairment, of whom 163 million (55%; 147-179) were female; 258 million (233-285) to have mild vision impairment, of whom 142 million (55%; 128-157) were female; and 510 million (371-667) to have visual impairment from uncorrected presbyopia, of whom 280 million (55%; 205-365) were female. Globally, between 1990 and 2020, among adults aged 50 years or older, age-standardised prevalence of blindness decreased by 28·5% (-29·4 to -27·7) and prevalence of mild vision impairment decreased slightly (-0·3%, -0·8 to -0·2), whereas prevalence of moderate and severe vision impairment increased slightly (2·5%, 1·9 to 3·2; insufficient data were available to calculate this statistic for vision impairment from uncorrected presbyopia). In this period, the number of people who were blind increased by 50·6% (47·8 to 53·4) and the number with moderate and severe vision impairment increased by 91·7% (87·6 to 95·8). By 2050, we predict 61·0 million (52·9 to 69·3) people will be blind, 474 million (428 to 518) will have moderate and severe vision impairment, 360 million (322 to 400) will have mild vision impairment, and 866 million (629 to 1150) will have uncorrected presbyopia. INTERPRETATION: Age-adjusted prevalence of blindness has reduced over the past three decades, yet due to population growth, progress is not keeping pace with needs. We face enormous challenges in avoiding vision impairment as the global population grows and ages. FUNDING: Brien Holden Vision Institute, Fondation Thea, Fred Hollows Foundation, Bill & Melinda Gates Foundation, Lions Clubs International Foundation, Sightsavers International, and University of Heidelberg.

Rats and mice exhibit a spontaneous attraction for lipids. Such a behavior raises the possibility that an orosensory system is responsible for the detection of dietary lipids. The fatty acid transporter CD36 appears to be a plausible candidate for this function since it has a high affinity for long-chain fatty acids (LCFAs) and is found in lingual papillae in the rat. To explore this hypothesis further, experiments were conducted in rats and in wild-type and CD36-null mice. In mice, RT-PCR experiments with primers specific for candidate lipid-binding proteins revealed that only CD36 expression was restricted to lingual papillae although absent from the palatal papillae. Immunostaining studies showed a distribution of CD36 along the apical side of circumvallate taste bud cells. CD36 gene inactivation fully abolished the preference for LCFA-enriched solutions and solid diet observed in wild-type mice. Furthermore, in rats and wild-type mice with an esophageal ligation, deposition of unsaturated LCFAs onto the tongue led to a rapid and sustained rise in flux and protein content of pancreatobiliary secretions. These findings demonstrate that CD36 is involved in oral LCFA detection and raise the possibility that an alteration in the lingual fat perception may be linked to feeding dysregulation.

To sense myriad environmental odors, animals have evolved multiple, large families of divergent olfactory receptors. How and why distinct receptor repertoires and their associated circuits are functionally and anatomically integrated is essentially unknown. We have addressed these questions through comprehensive comparative analysis of the Drosophila olfactory subsystems that express the ionotropic receptors (IRs) and odorant receptors (ORs). We identify ligands for most IR neuron classes, revealing their specificity for select amines and acids, which complements the broader tuning of ORs for esters and alcohols. IR and OR sensory neurons exhibit glomerular convergence in segregated, although interconnected, zones of the primary olfactory center, but these circuits are extensively interdigitated in higher brain regions. Consistently, behavioral responses to odors arise from an interplay between IR- and OR-dependent pathways. We integrate knowledge on the different phylogenetic and developmental properties of these receptors and circuits to propose models for the functional contributions and evolution of these distinct olfactory subsystems.

PURPOSE: Age-related macular degeneration (AMD) is a frequent, complex disorder in elderly of European ancestry. Risk profiles and treatment options have changed considerably over the years, which may have affected disease prevalence and outcome. We determined the prevalence of early and late AMD in Europe from 1990 to 2013 using the European Eye Epidemiology (E3) consortium, and made projections for the future. DESIGN: Meta-analysis of prevalence data. PARTICIPANTS: A total of 42 080 individuals 40 years of age and older participating in 14 population-based cohorts from 10 countries in Europe. METHODS: AMD was diagnosed based on fundus photographs using the Rotterdam Classification. Prevalence of early and late AMD was calculated using random-effects meta-analysis stratified for age, birth cohort, gender, geographic region, and time period of the study. Best-corrected visual acuity (BCVA) was compared between late AMD subtypes; geographic atrophy (GA) and choroidal neovascularization (CNV). MAIN OUTCOME MEASURES: Prevalence of early and late AMD, BCVA, and number of AMD cases. RESULTS: Prevalence of early AMD increased from 3.5% (95% confidence interval [CI] 2.1%-5.0%) in those aged 55-59 years to 17.6% (95% CI 13.6%-21.5%) in those aged ≥85 years; for late AMD these figures were 0.1% (95% CI 0.04%-0.3%) and 9.8% (95% CI 6.3%-13.3%), respectively. We observed a decreasing prevalence of late AMD after 2006, which became most prominent after age 70. Prevalences were similar for gender across all age groups except for late AMD in the oldest age category, and a trend was found showing a higher prevalence of CNV in Northern Europe. After 2006, fewer eyes and fewer ≥80-year-old subjects with CNV were visually impaired (P = 0.016). Projections of AMD showed an almost doubling of affected persons despite a decreasing prevalence. By 2040, the number of individuals in Europe with early AMD will range between 14.9 and 21.5 million, and for late AMD between 3.9 and 4.8 million. CONCLUSION: We observed a decreasing prevalence of AMD and an improvement in visual acuity in CNV occuring over the past 2 decades in Europe. Healthier lifestyles and implementation of anti-vascular endothelial growth factor treatment are the most likely explanations. Nevertheless, the numbers of affected subjects will increase considerably in the next 2 decades. AMD continues to remain a significant public health problem among Europeans.

BACKGROUND: Peptidergic neurons containing the melanin-concentrating hormone (MCH) and the hypocretins (or orexins) are intermingled in the zona incerta, perifornical nucleus and lateral hypothalamic area. Both types of neurons have been implicated in the integrated regulation of energy homeostasis and body weight. Hypocretin neurons have also been involved in sleep-wake regulation and narcolepsy. We therefore sought to determine whether hypocretin and MCH neurons express Fos in association with enhanced paradoxical sleep (PS or REM sleep) during the rebound following PS deprivation. Next, we compared the effect of MCH and NaCl intracerebroventricular (ICV) administrations on sleep stage quantities to further determine whether MCH neurons play an active role in PS regulation. RESULTS: Here we show that the MCH but not the hypocretin neurons are strongly active during PS, evidenced through combined hypocretin, MCH, and Fos immunostainings in three groups of rats (PS Control, PS Deprived and PS Recovery rats). Further, we show that ICV administration of MCH induces a dose-dependent increase in PS (up to 200%) and slow wave sleep (up to 70%) quantities. CONCLUSION: These results indicate that MCH is a powerful hypnogenic factor. MCH neurons might play a key role in the state of PS via their widespread projections in the central nervous system.

Juvenile hormone (JH) is a sesquiterpenoid of vital importance for insect development, yet the molecular basis of JH signaling remains obscure, mainly because a bona fide JH receptor has not been identified. Mounting evidence points to the basic helix-loop-helix (bHLH)/Per-Arnt-Sim (PAS) domain protein Methoprene-tolerant (Met) as the best JH receptor candidate. However, details of how Met transduces the hormonal signal are missing. Here, we demonstrate that Met specifically binds JH III and its biologically active mimics, methoprene and pyriproxyfen, through its C-terminal PAS domain. Substitution of individual amino acids, predicted to form a ligand-binding pocket, with residues possessing bulkier side chains reduces JH III binding likely because of steric hindrance. Although a mutation that abolishes JH III binding does not affect a Met-Met complex that forms in the absence of methoprene, it prevents both the ligand-dependent dissociation of the Met-Met dimer and the ligand-dependent interaction of Met with its partner bHLH-PAS protein Taiman. These results show that Met can sense the JH signal through direct, specific binding, thus establishing a unique class of intracellular hormone receptors.

Summary For food scientists and industrials, descriptive profiling is an essential tool that involves the evaluation of both the qualitative and quantitative sensory characteristics of a product by a panel. Recently, in response to industrial demands to develop faster and more cost‐effective methods of descriptive analysis, several methods have been offered as alternatives to conventional profiling. These methods can be classified in three families: (i) verbal‐based methods (flash profile and check‐all‐that‐apply), (ii) similarity‐based methods (free sorting task and projective mapping aka Napping ® ) and (iii) reference‐based methods (polarised sensory positioning and pivot profile). We successively present these three classes of methods in terms of origin, principles, statistical analysis, applications to food products, variations of the methods and the Pros and Cons.

BACKGROUND: Within a surveillance of the prevalence and causes of vision impairment in high-income regions and Central/Eastern Europe, we update figures through 2015 and forecast expected values in 2020. METHODS: Based on a systematic review of medical literature, prevalence of blindness, moderate and severe vision impairment (MSVI), mild vision impairment and presbyopia was estimated for 1990, 2010, 2015, and 2020. RESULTS: Age-standardised prevalence of blindness and MSVI for all ages decreased from 1990 to 2015 from 0.26% (0.10-0.46) to 0.15% (0.06-0.26) and from 1.74% (0.76-2.94) to 1.27% (0.55-2.17), respectively. In 2015, the number of individuals affected by blindness, MSVI and mild vision impairment ranged from 70 000, 630 000 and 610 000, respectively, in Australasia to 980 000, 7.46 million and 7.25 million, respectively, in North America and 1.16 million, 9.61 million and 9.47 million, respectively, in Western Europe. In 2015, cataract was the most common cause for blindness, followed by age-related macular degeneration (AMD), glaucoma, uncorrected refractive error, diabetic retinopathy and cornea-related disorders, with declining burden from cataract and AMD over time. Uncorrected refractive error was the leading cause of MSVI. CONCLUSIONS: While continuing to advance control of cataract and AMD as the leading causes of blindness remains a high priority, overcoming barriers to uptake of refractive error services would address approximately half of the MSVI burden. New data on burden of presbyopia identify this entity as an important public health problem in this population. Additional research on better treatments, better implementation with existing tools and ongoing surveillance of the problem is needed.

IMPORTANCE OF DIETARY FAT Evolutionary Perspectives on Fat Ingestion and Metabolism in Humans, William R. Leonard, J. Josh Snodgrass, and Marcia L. Robertson Pathophysiology and Evolutionary Aspects of Dietary Fats and Long-Chain Polyunsaturated Fatty Acids across the Life Cycle, Frits A.J. Muskiet TASTE OF FAT: FROM DETECTION TO BEHAVIOR Gustatory Mechanisms for Fat Detection, Timothy A. Gilbertson, Tian Yu, and Bhavik P. Shah Role of the Gustatory System in Fatty Acid Detection in Rats, David W. Pittman Peripheral Gustatory Processing of Free Fatty Acids, Jennifer M. Stratford and Robert J. Contreras Orosensory Factors in Fat Detection, James C. Smith Fat Taste in Humans: Is It a Primary? Richard D. Mattes NEURAL REPRESENTATIONS OF DIETARY FAT STIMULI Neural Representation of Fat Texture in the Mouth, Edmund T. Rolls Advantageous Object Recognition for High-Fat Food Images, Ulrike Toepel, Jean-Francois Knebel, Julie Hudry, Johannes le Coutre, and Micah M. Murray SENSORY APPEAL OF THE FAT-RICH DIET Preference for High-Fat Food in Animals, Yasuko Manabe, Shigenobu Matsumura, and Tohru Fushiki Human Perceptions and Preferences for Fat-Rich Foods, Adam Drewnowski and Eva Almiron-Roig CONTROL OF FOOD INTAKE AS A FUNCTION OF FAT Oral and Postoral Determinants of Dietary Fat Appetite, Karen Ackroff and Anthony Sclafani Control of Fat Intake by Striatal Opioids, Brian A. Baldo, Wayne E. Pratt, and Ann E. Kelley Fat-Rich Food Palatability and Appetite Regulation, Charlotte Erlanson-Albertsson Fats and Satiety, Rania Abou Samra GENETIC FACTORS INFLUENCING FAT PREFERENCE AND METABOLISM Heritable Variation in Fat Preference, Danielle R. Reed Dietary, Physiological, and Genetic Impacts on Postprandial Lipid Metabolism, Jose Lopez-Miranda and Carmen Marin LIPIDS AND DISEASE Control of Fatty Acid Intake and the Role of Essential Fatty Acids in Cognitive Function and Neurological Disorders, Kiran S. Panickar and Sam J. Bhathena What Is the Link between Docosahexaenoic Acid, Cognitive Impairment, and Alzheimer's Disease in the Elderly? Michel E. Begin, Melanie Plourde, Fabien Pifferi, and Stephen C. Cunnane Hypothalamic Fatty Acid Sensing in the Normal and Disease States, Madhu Chari, Carol K.L. Lam, and Tony K.T. Lam Dietary Fat and Carbohydrate Composition: Metabolic Disease, Marc A. Brown, Len H. Storlien, Xu-Feng Huang, Linda C. Tapsell, Paul L. Else, Janine A. Higgins, and Ian L. Brown Food Intake and Obesity: The Case of Fat, Jennifer T. Smilowitz, J. Bruce German, and Angela M. Zivkovic Index

Most living organisms use pheromones for inter-individual communication. In Drosophila melanogaster flies, several pheromones perceived either by contact/at a short distance (cuticular hydrocarbons, CHs), or at a longer distance (cis-vaccenyl acetate, cVA), affect courtship and mating behaviours. However, it has not previously been possible to precisely identify all potential pheromonal compounds and simultaneously monitor their variation on a time scale. To overcome this limitation, we combined Solid Phase Micro-Extraction with gas-chromatography coupled with mass-spectrometry. This allowed us (i) to identify 59 cuticular compounds, including 17 new CHs; (ii) to precisely quantify the amount of each compound that could be detected by another fly, and (iii) to measure the variation of these substances as a function of aging and mating. Sex-specific variation appeared with age, while mating affected cuticular compounds in both sexes with three possible patterns: variation was (i) reciprocal in the two sexes, suggesting a passive mechanical transfer during mating, (ii) parallel in both sexes, such as for cVA which strikingly appeared during mating, or (iii) unilateral, presumably as a result of sexual interaction. We provide a complete reassessment of all Drosophila CHs and suggest that the chemical conversation between male and female flies is far more complex than is generally accepted. We conclude that focusing on individual compounds will not provide a satisfactory understanding of the evolution and function of chemical communication in Drosophila.

Smelling monomolecular odors hardly ever occurs in everyday life, and the daily functioning of the sense of smell relies primarily on the processing of complex mixtures of volatiles that are present in the environment (e.g., emanating from food or conspecifics). Such processing allows for the instantaneous recognition and categorization of smells and also for the discrimination of odors among others to extract relevant information and to adapt efficiently in different contexts. The neurophysiological mechanisms underpinning this highly efficient analysis of complex mixtures of odorants is beginning to be unraveled and support the idea that olfaction, as vision and audition, relies on odor-objects encoding. This configural processing of odor mixtures, which is empirically subject to important applications in our societies (e.g., the art of perfumers, flavorists, and wine makers), has been scientifically studied only during the last decades. This processing depends on many individual factors, among which are the developmental stage, lifestyle, physiological and mood state, and cognitive skills; this processing also presents striking similarities between species. The present review gathers the recent findings, as observed in animals, healthy subjects, and/or individuals with affective disorders, supporting the perception of complex odor stimuli as odor objects. It also discusses peripheral to central processing, and cognitive and behavioral significance. Finally, this review highlights that the study of odor mixtures is an original window allowing for the investigation of daily olfaction and emphasizes the need for knowledge about the underlying biological processes, which appear to be crucial for our representation and adaptation to the chemical environment.

During eating, foods are submitted to two main oral processes-chewing, including biting and crushing with teeth, and progressive impregnation by saliva resulting in the formation of a cohesive bolus and swallowing of the bolus. Texture influences the chewing behavior, including mastication and salivation, and in turn, these parameters influence texture perception and bolus formation. During this complex mouth process, flavor compounds are progressively released from the food matrix. This phenomenon is mainly dependent on the food texture, the composition and in-mouth breakdown, and on saliva impregnation and activity, but an individual's anatomical and physiological aspects characteristics should also be taken into account. This article reviews the knowledge and progresses on in-mouth processes leading to food breakdown and flavor release and affecting perception. Relationships between food texture and composition, food breakdown, oral physiology, and flavor release are developed and discussed. This review includes not only the mechanical aspects of oral physiology but also the biological aspects such as the influence of saliva composition, activity, and regulation on flavor perception. In vitro and in silico approaches are also described.

PURPOSE OF REVIEW: This review summarizes and discusses the current knowledge about the physiological roles of the sweet taste receptor in oral and extraoral tissues. RECENT FINDINGS: The expression of a functional sweet taste receptor has been reported in numerous extragustatory tissues, including the gut, pancreas, bladder, brain and, more recently, bone and adipose tissues. In the gut, this receptor has been suggested to be involved in luminal glucose sensing, the release of some satiety hormones, the expression of glucose transporters, and the maintenance of glucose homeostasis. More recently, the sweet taste receptor was proposed to regulate adipogenesis and bone biology. SUMMARY: The perception of sweet taste is mediated by the T1R2/T1R3 receptor, which is expressed in the oral cavity, wherein it provides input on the caloric and macronutrient contents of ingested food. This receptor recognizes all the chemically diverse compounds perceived as sweet by human beings, including natural sugars and sweeteners. Importantly, the expression of a functional sweet taste receptor has been reported in numerous extragustatory tissues, wherein it has been proposed to regulate metabolic processes. This newly recognized role of the sweet taste receptor makes this receptor a potential novel therapeutic target for the treatment of obesity and related metabolic dysfunctions, such as diabetes and hyperlipidemia.

The sense of taste informs the body about the quality of ingested foods. Tastant‐mediated signals are generated by a rise in free intracellular calcium levels ([Ca 2+ ]i) in the taste bud cells and then are transferred to the gustatory area of brain via connections between the gustatory nerves (chorda tym‐ pani and glossopharyngeal nerves) and the nucleus of solitary tract in the brain stem. We have recently shown that lingual CD36 contributes to fat preference and early digestive secretions in the mouse. We show here that 1 ) the induction of an increase in [Ca 2+ ]i by linoleic acid is CD36‐dependent in taste receptor cells, 2) the spontaneous preference for or conversely con ditioned aversion to linoleic acid requires intact gusta tory nerves, and 3) the activation of gustatory neurons in the nucleus of the solitary tract elicited by a linoleic acid deposition on the tongue in wild‐type mice cannot be reproduced in CD36‐null animals. We conclude that the CD36‐mediated perception of long‐chain fatty acids involves the gustatory pathway, suggesting that the mouse may have a “taste“ for fatty foods. This system would constitute a potential physiological advantage under conditions of food scarcity by leading the mouse to select and absorb fatty foods. However, it might also lead to a risk of obesity and associated diseases in a context of constantly abundant food.—Gaillard, D., Laugerette, F., Darcel, N., El‐Yassimi, A., Passilly‐De grace, P., Hichami, A., Khan, N. A., Montmayeur, J.‐P., Besnard, P. The gustatory pathway is involved in CD36‐ mediated orosensory perception of long‐chain fatty acids in the mouse. FASEB J . 22, 1458–1468 (2008)

Juvenile hormones (JHs) play a major role in controlling development and reproduction in insects and other arthropods. Synthetic JH-mimicking compounds such as methoprene are employed as potent insecticides against significant agricultural, household and disease vector pests. However, a receptor mediating effects of JH and its insecticidal mimics has long been the subject of controversy. The bHLH-PAS protein Methoprene-tolerant (Met), along with its Drosophila melanogaster paralog germ cell-expressed (Gce), has emerged as a prime JH receptor candidate, but critical evidence that this protein must bind JH to fulfill its role in normal insect development has been missing. Here, we show that Gce binds a native D. melanogaster JH, its precursor methyl farnesoate, and some synthetic JH mimics. Conditional on this ligand binding, Gce mediates JH-dependent gene expression and the hormone's vital role during development of the fly. Any one of three different single amino acid mutations in the ligand-binding pocket that prevent binding of JH to the protein block these functions. Only transgenic Gce capable of binding JH can restore sensitivity to JH mimics in D. melanogaster Met-null mutants and rescue viability in flies lacking both Gce and Met that would otherwise die at pupation. Similarly, the absence of Gce and Met can be compensated by expression of wild-type but not mutated transgenic D. melanogaster Met protein. This genetic evidence definitively establishes Gce/Met in a JH receptor role, thus resolving a long-standing question in arthropod biology.