China has been described as a “rogue” donor suspected of usingforeign assistance to obtain raw materials, promote exports, and strengthenits business links with aid recipient countries. However, the factorsinfluencing China’s development assistance policy have rarely beenanalysed, particularly those related to its health aid. This study exploresthe factors that could affect the allocation of China’s developmentassistance for health (DAH) from three key aspects: recipient need,recipient merit, and donor interest.Analysis was based on cross-sectional data of China’s DAH from 2006 to2014. This study explores the following characteristics of the 82 recipientcountries identified in the data: the association between China’sallocation of DAH and recipient need ,recipient merit (measured by government effectiveness and human rightsviolations) and donor interests . A stratifiedanalysis was conducted to understand these associations in differentdevelopment contexts and the factors that influenced each type of DAH.r = -0.31941,P = 0.0049) and human rights conditions. Health workforce was associatedwith medical team deployment , while malaria DALYs wasassociated with anti-malaria center establishment. According to the sub-groupanalysis, donor interests such as trade and natural resources only slightlyinfluenced DAH allocation.Multivariate Spearman correlation suggested that the most significant factorsinfluencing China’s allocation of DAH were the recipientcountries’ GDP per capita(Recipient need and merit strongly influence China’s DAH allocationwhile donor interests only slightly influence DAH allocation in certaindevelopment contexts. The official development assistance (ODA) landscape has changed markedly in recentyears; the purpose, quantity, and modalities have evolved along with the identitiesof aid donors and recipients. In 2015, net ODA from members of the DevelopmentAssistance Committee (DAC) of the Organization for Economic Co-operation and Development(OECD) reached 146.68 billion US$, the highest real level of ODA recorded [Past studies have concluded that ODA allocation rationale is not limited to developingcountries’ needs but also includes donor self-interest. A recipient country'sincome level and humanitarian needs are certainly factors shaping the allocation of DACaid . There a(1) Donor Interests: the interests of donor countries when deploying aid, includingbenefits in trade and commerce, foreign policy, etc.(2) Recipient Need: the level of development assistance need of a recipient country,including overarching development needs such as poverty reduction and peace-building aswell as aid-specific needs such as disease burden reduction.(3) Recipient Merit: the quality of policies and institutions in a recipient country,given that a recipient's economic policies and system of government may affectdonor aid allocation.China has a long history of deploying foreign aid as an indispensable component of itsforeign diplomacy. Since 1950, the Chinese government has provided various forms offoreign aid to 160 countries and over 30 international organizations . China'sChina's health-related development assistance has traditionally taken three forms:medical teams, infrastructure, and knowledge transfer . China hHowever, the intentions driving China’s foreign aid allocation strategies haveoften been questioned. China is suspected of obtaining raw materials, promoting exportedproducts, and strengthening business linkages with recipient countries in exchange foraid . Naím chChina’s health-related assistance has not been without criticism. Health-specificaid has also been considered a Chinese commercial policy tool, as the Chinese stateenterprises has been largely involved in the DAH process; domestic pharmaceuticalfirms have provided their products as “health aid”, which could potentiallyexpand the market share of Chinese pharmaceutical products in settings such as Africa. Often uFew study have used a quantitative approach to either support or refute these claims ofChinese aid allocation, which may partly be due to limited data sources on China’sDAH. Existing literature suggests that there is no relationship between China’sDAH and a recipient country’s natural resources  but showThis paper aims to analyse the associations of China’s DAH allocation withrecipient need, recipient merits and donor interests to explore the factors thatinfluence China’s DAH allocation. The results of this study are of vitalimportance to expand existing knowledge of China’s DAH allocation.Our model used cross-sectional data from 2006-2014. 137 ODA recipient countrieswere identified  [The outcome variable in this study was China’s DAH level to all recipientcountries before 2011. DAH level refers to the cumulative types of health aid,including “medical team deployment”, “hospitalconstruction” and “anti-malaria center construction”. In thisstudy, the DAH level index is defined as a three-scale indicator :“1” refers to one kind of aid;“2” refers to the combination of two types of aid;“3” refers to the provision of all three types of aid.AidData – the first systematic and only publicly available database onChina’s development aid – is the source of this study’s data.Health-related project-level data was extracted from the database, and the DAHlevel index was calculated accordingly. Data was further validated by expertinterviews and internal material from China National Health Development ResearchCenter .Based on the information available from earlier studies, our allocation modelincludes three categories of explanatory variables: recipient need, recipientmerit, and donor self-interest (Five indicators were included: the former two indicators (1a and 1b) wereused for general analysis and the latter three  were used intype-specific analysis.(1a) Recipient Gross Domestic Product (GDP) per capita was retrievedfrom the World Development Indicators Database and was defined asthe average GDP per capita from 2006 to 2014 in current US$.(1b) Recipient age-standardized Disability Adjusted Life Years(DALYs) is an indicator commonly used to quantify the burden ofdisease from mortality and morbidity. Data was obtained from theIHME Global Burden of Disease 2010 study .(1c) Recipient country health workforce was retrieved from the WorldHealth Statistics , whichw(1d) Recipient country hospital beds was retrieved from the WorldHealth Statistics, which was defined as the recipientcountry’s hospital beds number per 10 000 population,from 2000-2009.(1e) Recipient countries’ malaria DALYs, which was themalaria-specific burden of disease retrieved from the IHME study.(2a) Recipient country government effectiveness data was measuredusing index developed by Kaufmann . The ind(2b) Human rights violations data were retrieved from the PoliticalTerror Scale’s data in 2011. The index is measured on a scaleof 1 to 5, with higher numbers indicating more human rights abuses[(3a) Trade level was defined as the flow of China’s export to arecipient, as a percentage of recipient’s overall imports in2011, using data from UN Comtrade.(3b) Voting alignment in the UN, which is a commonly used indicatorwas attained by China and the recipient countries’ votingaffinity at the UN General Assembly from 2006 to 2014, value rangedfrom –1 (least similar interests) to 1 (most similarinterests). The detailed methodology of this indicator could befound in Signorino and Ritter’s study .(3c) Recipient country natural resource was defined as the sum of oilrents, natural gas rents, coal rents (hard and soft), mineral rents,and forest rents, as a percentage of recipient GDP from 2006 to2014. Data was retrieved from the World Development IndicatorsDatabase.Univariate analyses were conducted using the Spearman rank correlation tounderstand the association between each influencing factor and DAH level.Spearman correlation was further conducted to understand whether recipient GDPper capita, recipient DALYs, recipient government effectiveness, recipient humanrights violations, trade level, voting alignment at UN, and/or recipient naturalresource rent influence China’s allocation of DAH (the DAH level), whileadjusting for each other.To evaluate the modifying effects of recipient development status, stratifiedanalyses were performed under each development stage. Based on OECDclassification, countries were categorized according to per capita GNI into thefollowing three groups: least developed countries (n = 41),low-income countries and lower middle-income countries and territories, and uppermiddle-income countries and territories  [P < 0.05 andP < 0.1 levels.All statistical analyses were performed using SAS Version 9.3 , and significant test results were reported atBetween 1963 and 2011, a total of 82 countries were identified as recipient countriesof China’s development assistance for health; among them, 41 countrieswere least developed countries (LDCs) according to the OECD definition. Of the 82recipient countries, 26 received all three types of health aid , 20countries received two types of aid, and 36 countries received one type of healthaid  and multivariate analysis. Recipient country all-cause DALYs, government effectiveness, and natural resource rent were significantly associated with healthaid level in the univariate analysis, but were insignificant in the multivariateanalysis . Recipient country humanrights violations was insignificant in the univariate analysis but was significant in the multivariateanalysis .P level of 0.0491,indicating that a lower trade level was significantly associated with more healthaid.Stratified analysis was conducted to fully evaluate the modifying effect of recipientdevelopment status on China’s allocation of its development assistance forhealth . In contrast, China’s hospitalconstruction was independent of all influencing factors, including the density ofhospital beds of the recipient country . As for China’s anti-malariacenters, the recipient country’s malaria DALYs significantly influencedChina’s DAH allocation . Human rights violations were alsonegatively associated with the establishment of a China’s anti-malaria center.Finally, the associations between various factors influencing China’s DAH andeach health aid type was analyzed; The present study is one of the few studies that analyzed China’s allocation ofDAH using a quantitative approach. This study indicates that China allocated morehealth aid to countries with stronger development needs and better merit in terms ofgood governance and human rights records. We found no evidence that China’sDAH was directly associated with bilateral trade or UN voting affinity. There was aweak association between China’s DAH and natural resource rent, whichdiminished after adjusting for other confounding factors. Although China has beensuspected of using foreign assistance to obtain raw materials, promote domesticexportations and strengthen its business ties with recipient countries, suchsuspicion appears to be invalid at least in the health sector.This paper offers several contributions to existing knowledge on China’sDAH. First, this study collected the best available information on China’said channel and volume. Second, despite the similarity between health and othersocial development sectors like agriculture and education, DAH has largely beenneglected by researchers of development aid. This paper provides an empiricalanalysis of factors determining the allocation of health aid, and explains thepolitical and economic influence of DAH.There are several potential limitations of the present study. First, the levelsof China’s DAH was measured as a three-scale indicator rather than theactual volume of aid allocated. This was largely due to insufficient data, andthe uncertainty in the accuracy of total aid volume provided in AidData, wherewe identified 40% of health projects had missing values. On one hand, using DAHlevel instead of total volume might not appropriately reflect the extent ofChina’s development assistance given that concessional loans and otherdevelopment assistance for health  were notincluded. On the other, arbitrarily using categorical average to fill outmissing value may lead to bias. In general, considering that there was noofficial data of China’s overseas development aid, these surrogate DAHlevel indicators were the best-available evidence for the present analyses.Second, also due to limited data, the author only used cross-sectional analyses,which cannot provide a cauxal relation of the influencing factors andChina’s allocation of DAH.This study found that a recipient country’s GDP per capita and healthstatus may influence China’s DAH allocation, as both recipient GDP percapita and DALYs were significantly associated with DAH allocation. It was foundthat significantly more health aid was allocated to least developed countries.In addition, evidence suggested that medical teams were sent to countries withpoor health human resources and anti-malaria centers were established incountries with a high malaria burden. This shows that China’s health aidallocation was, to a certain extent, guided by recipient needs, which alignswith China’s recipient-driven mechanism indicated in the “FivePrinciples of Peaceful Coexistence” . MeanwhiGovernment effectiveness was negatively associated with DAH level, and humanrights violations were also a significant influencing factor of DAHallocation; sub-group analysis indicated that human rights violations werealso associated with anti-malaria center allocation. It should be emphasizedthat in the political terror scale data set—which we use as a measure ofhuman rights – higher positive values are associated with greater abuse ofpolitical rights. The negative coefficient for human rights violation with DAHlevel indicates that China’s health aid concentrates in politicalenvironments with a greater respect for human rights.Recipient merit such as government policies and human rights records areimportant factors for many traditional donors. Countries such as France,Germany, and Japan all take human rights abuses into account when allocatingforeign aid. Another example is the UK, which rewards good economic policies anddemocracies . Some doDifferent from western donors, China’s DAH reflects China’s“non-interference” principle - “not imposing any politicalconditions nor interfering in the affairs of the recipient countries”. This apOur study found that bilateral trade was associated with DAH allocation only inupper middle-income countries, while the negative coefficient suggested thatmore health aid flew to countries with weaker trade relations with China. It hasalways been hypothesized that China has used DAH as a brokerage to promotebilateral trade . It’s woFor political considerations, past research has shown strong evidence thatpolitics plays an important role in the allocation of aid money and medicalstaff to recipient countries in all phases of China’s aid program . HoweverOur study found that a recipient country’s natural resources were notassociated with DAH allocation after adjusting for other confounders; thisfinding is consistent with the analysis of Grépin et al . AdditioChina is neither a signatory member of the Paris Declaration on Aid Effectivenessnor committed to the Busan Partnership for Effective Development Cooperation ona “voluntary basis” ,which iBy exploring the potential factors that could affect the allocation of China’sdevelopment assistance for health, this study shows that China allocated more healthaid to countries with stronger development needs and stronger recipient merit interms of good governance and human rights records. We found no direct evidence thatChina’s DAH was directly associated with bilateral trade or UN votingaffinity.


Although the Concise Guide represents approximately 400 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point‐in‐time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.14747. In addition to this overview, in which are identified Other protein targets which fall outside of the subsequent categorisation, there are six areas of focus: G protein‐coupled receptors, ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid‐2019, and supersedes data presented in the 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the International Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification (NC‐IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.The Concise Guide to PHARMACOLOGY 2019/20 is the fourth in this series of biennial publications. The Concise Guide provides concise overviews of the key properties of nearly 1800 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands ( Thyroid hormone receptorsS231 1B. Retinoic acid receptorsS232 1C. Peroxisome proliferator‐activated receptorsS233 1D. Rev‐Erb receptorsS234 1F. Retinoic acid‐related orphansS234 1H. Liver X receptor‐like receptorsS235 1I. Vitamin D receptor‐like receptorsS236 2A. Hepatocyte nuclear factor‐4 receptorsS237 2B. Retinoid X receptorsS238 2C. Testicular receptorsS238 2E. Tailless‐like receptorsS239 2F. COUP‐TF‐like receptorsS239 3B. Estrogen‐related receptorsS240 4A. Nerve growth factor IB‐like receptorsS241 5A. Fushi tarazu F1‐like receptorsS241 6A. Germ cell nuclear factor receptorsS242 0B. DAX‐like receptorsS242 Steroid hormone receptorsS243 3A. Estrogen receptorsS244 3C. 3‐Ketosteroid receptorsS248 Cytokine receptor familyS249 IL‐2 receptor familyS251 IL‐3 receptor familyS252 IL‐6 receptor familyS254 IL‐12 receptor familyS255 Prolactin receptor familyS256 Interferon receptor familyS257 IL‐10 receptor familyS258 Immunoglobulin‐like family of IL‐1 receptorsS259 IL‐17 receptor familyS259 GDNF receptor familyS260 IntegrinsS264 Pattern recognition receptorsS264 Toll‐like receptor familyS266 NOD‐like receptor familyS268 RIG‐I‐like receptor familyS269 Receptor Guanylyl Cyclase (RGC) familyS269 Transmembrane quanylyl cyclasesS270 Nitric oxide (NO)‐sensitive (soluble) guanylyl cyclaseS271 Receptor tyrosine kinases (RTKs)S272 Type I RTKs: ErbB  receptor familyS273 Type II RTKs: Insulin receptor familyS274 Type III RTKs: PDGFR, CSFR, Kit, FLT3 receptor familyS275 Type IV RTKs: VEGF  receptor familyS275 Type V RTKs: FGF (broblast growth factor) receptor familyS276 Type VI RTKs: PTK7/CCK4S277 Type VII RTKs: Neurotrophin receptor/Trk familyS278 Type VIII RTKs: ROR familyS278 Type IX RTKs: MuSKS279 Type X RTKs: HGF (hepatocyte growth factor) receptor familyS279 Type XI RTKs: TAM  receptor familyS280 Type XII RTKs: TIE family of angiopoietin receptorsS280 Type XIII RTKs: Ephrin receptor familyS281 Type XIV RTKs: RETS282 Type XV RTKs: RYKS282 Type XVI RTKs: DDR (collagen receptor) familyS283 Type XVII RTKs: ROS receptorsS283 Type XVIII RTKs: LMR familyS284 Type XIX RTKs: Leukocyte tyrosine kinase (LTK) receptor familyS284 Type XX RTKs: STYK1S286 Receptor serine/threonine kinase (RSTK) familyS286 Type I receptor serine/threonine kinasesS287 Type II receptor serine/threonine kinasesS287 Type III receptor serine/threonine kinasesS287 RSTK functional heteromersS289 Receptor tyrosine phosphatase (RTP) familyS291 Tumour necrosis factor (TNF) receptor familyS301 Acetylcholine turnoverS302 Adenosine turnoverS303 Amino acid hydroxylasesS304 L‐Arginine turnoverS304 2.1.1.‐ Protein arginine N‐methyltransferasesS305 ArginaseS305 Arginine:glycine amidinotransferaseS305 Dimethylarginine dimethylaminohydrolasesS306 Nitric oxide synthasesS307 Carbonic anhydrasesS308 Carboxylases and decarboxylasesS308 CarboxylasesS309 DecarboxylasesS311 Catecholamine turnoverS313 Ceramide turnoverS313 Serine palmitoyltransferaseS314 Ceramide synthase4‐desaturaseS314 Sphingolipid ΔS315 Sphingomyelin synthaseS315 Sphingomyelin phosphodiesteraseS316 Neutral sphingomyelinase coupling factorsS316 Ceramide glucosyltransferaseS316 Acid ceramidaseS317 Neutral ceramidasesS317 Alkaline ceramidasesS318 Ceramide kinaseS319 Chromatin modifying enzymesS319 2.1.1.‐ Protein arginine N‐methyltransferasesS320 3.5.1.‐ Histone deacetylases (HDACs)S321 Cyclic nucleotide turnover/signallingS321 Adenylyl cyclases (ACs)S323 Exchange protein activated by cyclic AMP (EPACs)S323 Phosphodiesterases, 3’,5’‐cyclic nucleotide (PDEs)S327 Cytochrome P450S327 CYP2 familyS328 CYP2 familyS329 CYP3 familyS330 CYP4 familyS331 CYP5, CYP7 and CYP8 familiesS332 CYP11, CYP17, CYP19, CYP20 and CYP21 familiesS333 CYP24, CYP26 and CYP27 familiesS333 CYP39, CYP46 and CYP51 familiesS334 DNA topoisomerasesS335 Endocannabinoid turnoverN‐Acylethanolamine turnoverS336 S337 2‐Acylglycerol ester turnoverS338 Eicosanoid turnoverS338 CyclooxygenaseS339 Prostaglandin synthasesS341 LipoxygenasesS342 Leukotriene and lipoxin metabolismS343 GABA turnoverS344 Glycerophospholipid turnoverS345 Phosphoinositide‐specific phospholipase C2S346 Phospholipase AS348 Phosphatidylcholine‐specific phospholipase DS349 Lipid phosphate phosphatasesS349 Phosphatidylinositol kinasesS350 1‐phosphatidylinositol 4‐kinase familyS351 Phosphatidylinositol‐4‐phosphate 3‐kinase familyS351 Phosphatidylinositol 3‐kinase familyS351 Phosphatidylinositol‐4,5‐bisphosphate 3‐kinase familyS352 1‐phosphatidylinositol‐3‐phosphate 5‐kinase familyS353 Type I PIP kinases (1‐phosphatidylinositol‐4‐phosphate 5‐kinase family)S353 Type II PIP kinases (1‐phosphatidylinositol‐5‐phosphate 4‐kinase family)S356 Phosphatidylinositol phosphate kinasesS356 Haem oxygenaseS358 Hydrogen sulphide synthesisS358 HydrolasesS360 Inositol phosphate turnoverS360 Inositol 1,4,5‐trisphosphate 3‐kinasesS360 Inositol polyphosphate phosphatasesS361 Inositol monophosphataseS361 Kinases (EC 2.7.x.x)S362 Rho kinaseS362 Protein kinase C (PKC) familyS363 Alpha subfamilyS363 Delta subfamilyS364 Eta subfamilyS364 FRAP subfamilyS365 Cyclin‐dependent kinase (CDK) familyS365 CDK4 subfamilyS366 GSK subfamilyS367 Polo‐like kinase (PLK) familyS367 STE7 familyS368 Abl familyS368 Ack familyS369 Janus kinase (JakA) familyS369 Src familyS370 Tec familyS371 RAF familyS372 Lanosterol biosynthesis pathwayS374 Nucleoside synthesis and metabolismS376 Paraoxonase (PON) familyS377 Peptidases and proteinasesS377 A1: PepsinS377 A22: PresenilinS378 C14: CaspaseS378 M1: Aminopeptidase NS379 M2: Angiotensin‐converting (ACE and ACE2)S379 M10: Matrix metallopeptidaseS380 M12: Astacin/AdamalysinS380 M28: Aminopeptidase YS381 M19: Membrane dipeptidaseS381 S1: ChymotrypsinS382 T1: ProteasomeS382 S8: SubtilisinS383 S9: Prolyl oligopeptidaseS383 Poly ADP‐ribose polymerasesS384 Prolyl hydroxylasesS384 Sphingosine 1‐phosphate turnoverS385 Sphingosine kinaseS386 Sphingosine 1‐phosphate phosphataseS387 Sphingosine 1‐phosphate lyaseS387 Thyroid hormone turnoverS388 1.14.13.9 Kynurenine 3‐monooxygenaseS389 2.5.1.58 Protein farnesyltransferaseS390 3.5.1.‐ Histone deacetylases (HDACs)S391 3.5.3.15 Peptidyl arginine deiminases (PADI)S391 3.6.5.2 Small monomeric GTPasesS391 RAS subfamilyS392 RAB subfamilyS399 ATP‐binding cassette transporter familyS399 ABCA subfamilyS401 ABCB subfamilyS403 ABCC subfamilyS404 ABCD subfamily of peroxisomal ABC transportersS405 ABCG subfamilyS406 F‐type and V‐type ATPasesS406 F‐type ATPaseS407 V‐type ATPaseS407 P‐type ATPases+/K+‐ATPasesS407 Na2+‐ATPasesS408 Ca+/K+‐ATPasesS408 H+‐ATPasesS408 CuS409 Phospholipid‐transporting ATPasesS409 SLC superfamily of solute carriersS410 SLC1 family of amino acid transportersS410 Glutamate transporter subfamilyS412 Alanine/serine/cysteine transporter subfamilyS413 SLC2 family of hexose and sugar alcohol transportersS413 Class I transportersS414 Class II transportersS415 Proton‐coupled inositol transporterS415 SLC3 and SLC7 families of heteromeric amino acid transporters (HATs)S415 SLC3 familyS416 SLC7 familyS417 SLC4 family of bicarbonate transportersS417 Anion exchangers3− transportersS418 Sodium‐dependent HCOS418 SLC5 family of sodium‐dependent glucose transportersS419 Hexose transporter familyS420 Choline transporterS421 Sodium iodide symporter, sodium‐dependent multivitamin transporter and sodium‐coupled monocarboxylate transportersmyo‐inositol cotransporter transportersS422 Sodium S423 SLC6 neurotransmitter transporter familyS423 Monoamine transporter subfamilyS424 GABA transporter subfamilyS425 Glycine transporter subfamilyS427 Neutral amino acid transporter subfamilyS428 SLC8 family of sodium/calcium exchangersS429 SLC9 family of sodium/hydrogen exchangersS429 SLC10 family of sodium‐bile acid co‐transportersS431 SLC11 family of proton‐coupled metal ion transportersS431 SLC12 family of cation‐coupled chloride transportersS433 SLC13 family of sodium‐dependent sulphate/carboxylate transportersS434 SLC14 family of facilitative urea transportersS435 SLC15 family of peptide transportersS437 SLC16 family of monocarboxylate transportersS438 SLC17 phosphate and organic anion transporter familyS438 Type I sodium‐phosphate co‐transportersS439 Sialic acid transporterS439 Vesicular glutamate transporters (VGLUTs)S440 Vesicular nucleotide transporterS440 SLC18 family of vesicular amine transportersS442 SLC19 family of vitamin transportersS443 SLC20 family of sodium‐dependent phosphate transportersS443 SLC22 family of organic cation and anion transportersS444 Organic cation transporters (OCT)S445 Organic zwitterions/cation transporters (OCTN)S446 Organic anion transporters (OATs)S446 Urate transporterS447 Atypical SLC22B subfamilyS448 SLC23 family of ascorbic acid transportersS449 SLC24 family of sodium/potassium/calcium exchangersS450 SLC25 family of mitochondrial transportersS450 Mitochondrial di‐ and tri‐carboxylic acid transporter subfamilyS451 Mitochondrial amino acid transporter subfamilyS452 Mitochondrial phosphate transportersS452 Mitochondrial nucleotide transporter subfamilyS453 Mitochondrial uncoupling proteinsS454 Miscellaneous SLC25 mitochondrial transportersS454 SLC26 family of anion exchangersS454 Selective sulphate transportersS455 Chloride/bicarbonate exchangersS455 Anion channelsS456 Other SLC26 anion exchangersS457 SLC27 family of fatty acid transportersS458 SLC28 and SLC29 families of nucleoside transportersS458 SLC28 familyS459 SLC29 familyS461 SLC30 zinc transporter familyS461 SLC31 family of copper transportersS462 SLC32 vesicular inhibitory amino acid transporterS463 SLC33 acetylCoA transporterS464 SLC34 family of sodium phosphate co‐transportersS465 SLC35 family of nucleotide sugar transportersS466 SLC36 family of proton‐coupled amino acid transportersS468 SLC37 family of phosphosugar/phosphate exchangersS468 SLC38 family of sodium‐dependent neutral amino acid transportersS469 System A‐like transportersS469 System N‐like transportersS470 Orphan SLC38 transportersS470 SLC39 family of metal ion transportersS471 SLC40 iron transporterS472 SLC41 family of divalent cation transportersS473 SLC42 family of Rhesus glycoprotein ammoniumtransportersS473 SLC43 family of large neutral amino acid transportersS474 SLC44 choline transporter‐like familyS475 SLC45 family of putative sugar transportersS475 SLC46 family of folate transportersS477 SLC47 family of multidrug and toxin extrusion transportersS477 SLC48 heme transporterS478 SLC49 family of FLVCR‐related heme transportersS479 SLC50 sugar transporterS479 SLC51 family of steroid‐derived molecule transportersS480 SLC52 family of riboflavin transportersS481 SLC53 Phosphate carriersS481 SLC54 Mitochondrial pyruvate carriersS482 SLC55 Mitochondrial cation/proton exchangersS482 SLC56 SideroflexinsS483 SLC57 NiPA‐like magnesium transporter familyS483 SLC58 MagT‐like magnesium transporter familyS484 SLC59 Sodium‐dependent lysophosphatidylcholine symporter familyS484 SLC60 Glucose transportersS485 SLC61 Molybdate transporter familyS485 SLC62 Pyrophosphate transportersS486 SLC63 Sphingosine phosphate transportersS486 SLC64 Golgi Ca2+/H+ exchangersS487 SLC65 NPC‐type cholesterol transportersS488 SLCO family of organic anion transporting polypeptideshttps://www.guidetopharmacology.org/). This database is supported by the British Pharmacological Society (BPS), the International Union of Basic and Clinical Pharmacology (IUPHAR), the University of Edinburgh and previously the Wellcome Trust. Data included in the Guide to PHARMACOLOGY are derived in large part from interactions with the subcommittees of the Nomenclature Committee of the International Union of Basic and Clinical Pharmacology (NC‐IUPHAR). A major influence on the development of the database was Tony Harmar (1951‐2014), who worked with a passion to establish the curators as a team of highly informed and informative individuals, with a focus on high‐quality data input, ensuring a suitably validated dataset. The Editors of the Concise Guide have compiled the individual records, in concert with the team of Curators, drawing on the expert knowledge of these latter subcommittees. The tables allow an indication of the status of the nomenclature for the group of targets listed, usually previously published in Pharmacological Reviews. In the absence of an established subcommittee, advice from several prominent, independent experts has generally been obtained to produce an authoritative consensus on nomenclature, which attempts to fit in within the general guidelines from NC‐IUPHAR. This current edition, the Concise Guide to PHARMACOLOGY 2019/20, is the latest snapshot of the database in print form, following on from the Concise Guide to PHARMACOLOGY 2017/18. It contains data drawn from the online database as a rapid overview of the major pharmacological targets. Thus, there are many fewer targets presented in the Concise Guide compared to the online database. The priority for inclusion in the Concise Guide is the presence of quantitative pharmacological data for human proteins. This means that often orphan family members are not presented in the Concise Guide, although structural information is available on the online database. The organisation of the data is tabular (where appropriate) with a standardised format, where possible on a single page, intended to aid understanding of, and comparison within, a particular target group. The Concise Guide is intended as an initial resource, with links to additional reviews and resources for greater depth and information. Pharmacological and structural data focus primarily on human gene products, wherever possible, with links to HGNC gene nomenclature and UniProt IDs. In a few cases, where data from human proteins are limited, data from other species are indicated. Pharmacological tools listed are prioritised on the basis of selectivity and availability. That is, agents  are included where they are both available  AND the most selective. The Concise Guide is divided into seven sections, which comprise pharmacological targets of similar structure/function. These are G protein‐coupled receptors, ion channels , catalytic receptors, nuclear hormone receptors, enzymes, transporters and other protein targets. We hope that the Concise Guide will provide for researchers, teachers and students a state‐of‐the art source of accurate, curated information on the background to their work that they will use in the Introductions to their Research Papers or Reviews, or in supporting their teaching and studies. We recommend that any citations to information in the Concise Guide are presented in the following format: Alexander SPH et al. (2019). The Concise Guide to PHARMACOLOGY 2019/20: Introduction and Other Protein Targets. Br J Pharmacol 176: S1–S20. In this overview are listed protein targets of pharmacological interest, which are not G protein‐coupled receptors, ion channels, nuclear hormone receptors, catalytic receptors, transporters or enzymes.In order to allow clarity and consistency in pharmacology, there is a need for a comprehensive organisation and presentation of the targets of drugs. This is the philosophy of the IUPHAR/BPS Guide to PHARMACOLOGY presented on the online free access database  also supported the initiation and expansion of the database. We are also tremendously grateful to the long list of collaborators from NC‐IUPHAR subcommittees and beyond, who have assisted in the construction of the Concise Guide to PHARMACOLOGY 2019/20 and the online database http://www.guidetopharmacology.org.We are extremely grateful to the British Pharmacological Society and the International Union of Basic and Clinical Pharmacology, for financial support of the website and for advice from the NC‐IUPHAR subcommittees. We thank the University of Edinburgh, who host the The authors state that there are no conflicts of interest to disclose.http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=1021– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=982– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=970– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=983– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=971– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=910– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=866– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=966– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=997– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=998– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=986– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=901– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=916– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=930– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=915– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=946– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=935– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=784– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=954– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=949– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=985– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=987– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=984– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=868– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=889– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=876– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=888– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=934– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=924– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=919– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=921– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=991– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=941– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=942– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=945– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=929– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=1001– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=906– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=907– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=932– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=905– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=875– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=1000– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=989– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=972– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=1019– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=973– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=974– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=990– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=995– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=996– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=904– http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=903– provisional nomenclature, http://www.ensembl.org/Homo_sapiens/Gene/Family/Genes?family=ENSFM00500000270960) respond to the 30 kDa complement‐related protein hormone adiponectin  originally cloned from adipocytes [http://www.ncbi.nlm.nih.gov/pubmed/8619847?dopt=AbstractPlus]. Although sequence data suggest 7TM domains, immunological evidence indicates that, contrary to typical 7TM topology, the carboxyl terminus is extracellular, while the amino terminus is intracellular [http://www.ncbi.nlm.nih.gov/pubmed/12802337?dopt=AbstractPlus]. Signalling through these receptors appears to avoid G proteins; modelling based on the crystal structures of the adiponectin receptors suggested ceramidase acivity, which would make these the first in a new family of catalytic receptors [http://www.ncbi.nlm.nih.gov/pubmed/25855295?dopt=AbstractPlus].Adiponectin receptors  has also been suggested to be a receptor for (hexameric) adiponectin [http://www.ncbi.nlm.nih.gov/pubmed/15210937?dopt=AbstractPlus].T‐Cadherin  Adiponectin: a manifold therapeutic target for metabolic syndrome, diabetes, and coronary disease? Cardiovasc Diabetol13: 103 [https://www.ncbi.nlm.nih.gov/pubmed/24957699?dopt=AbstractPlus]Fisman EZ et al. (2018) Structure and function analysis of adiponectin receptors toward development of novel antidiabetic agents promoting healthy longevity. Endocr J65: 971‐977 [https://www.ncbi.nlm.nih.gov/pubmed/30282888]Okada‐Iwabu M et al. (2016) Adiponectin signaling and function in insulin target tissues. J Mol Cell Biol8: 101‐9 [https://www.ncbi.nlm.nih.gov/pubmed/26993044?dopt=AbstractPlus]Ruan H et al. (2017) Cardiovascular Adiponectin Resistance: The Critical Role of Adiponectin Receptor Modification. Trends Endocrinol. Metab.28: 519‐530 [https://www.ncbi.nlm.nih.gov/pubmed/28473178?dopt=AbstractPlus]Wang Y et al. (2014) Adiponectin and insulin cross talk: the microvascular connection. Trends Cardiovasc. Med.24: 319‐24 [https://www.ncbi.nlm.nih.gov/pubmed/25220977?dopt=AbstractPlus]Zhao L http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=760), degranulation and aggregation of platelets, as well as proteins circulating in the plasma. The coagulation cascade involves multiple proteins being converted to more active forms from less active precursors, typically through proteolysis (see http://www.guidetopharmacology.org/GRAC/FamilyDisplayForward?familyId=759&familyType=ENZYME). Listed here are the components of the coagulation cascade targetted by agents in current clinical usage.Coagulation as a process is interpreted as a mechanism for reducing excessive blood loss through the generation of a gel‐like clot local to the site of injury. The process involves the activation, adhesion (see Blood125: 2045‐51 [https://www.ncbi.nlm.nih.gov/pubmed/25712994?dopt=AbstractPlus]Astermark J. (2015) FVIII inhibitors: pathogenesis and avoidance. et al. (2017) New clotting disorders that cast new light on blood coagulation and may play a role in clinical practice. J. Thromb. Thrombolysis44: 71‐75 [https://www.ncbi.nlm.nih.gov/pubmed/28251495?dopt=AbstractPlus]Girolami A et al. (2016) Blood flow and mass transfer regulation of coagulation. Blood Rev.30: 357‐68 [https://www.ncbi.nlm.nih.gov/pubmed/27133256?dopt=AbstractPlus]Rana K Bromodomains bind proteins with acetylated lysine residues, such as histones, to regulate gene transcription. Listed herein are examples of bromodomain‐containing proteins for which sufficient pharmacology exists.et al. (2017) Functions of bromodomain‐containing proteins and their roles in homeostasis and cancer. Nat. Rev. Mol. Cell Biol.18: 246‐262 [https://www.ncbi.nlm.nih.gov/pubmed/28053347?dopt=AbstractPlus]Fujisawa T Biochem Pharmacol159: 40‐51 [https://www.ncbi.nlm.nih.gov/pubmed/30414936]Myrianthopoulos V & Mikros E. (2019) From bench to bedside, via desktop. Recent advances in the application of cutting‐edge in silico tools in the research of drugs targeting bromodomain modules. et al. (2017) BET bromodomain proteins and epigenetic regulation of inflammation: implications for type 2 diabetes and breast cancer. Cell. Mol. Life Sci.74: 231‐243 [https://www.ncbi.nlm.nih.gov/pubmed/27491296?dopt=AbstractPlus]Nicholas DA Drug Discov Today23: 76‐89 [https://www.ncbi.nlm.nih.gov/pubmed/28943305]Ramadoss M & Mahadevan V. (2018) Targeting the cancer epigenome: synergistic therapy with bromodomain inhibitors. et al. (2019) Small‐molecule PROTAC degraders of the Bromodomain and Extra Terminal (BET) proteins ‐ A review. Drug Discov Today Technol31: 43‐51 [https://www.ncbi.nlm.nih.gov/pubmed/31200858]Yang CY http://www.ncbi.nlm.nih.gov/pubmed/23716704?dopt=AbstractPlus]. These amyloidogenic mutants are linked to the development of pathological amyloidoses, including familial amyloid polyneuropathy (FAP) , familial amyloid cardiomyopathy (FAC) [http://www.ncbi.nlm.nih.gov/pubmed/9017939?dopt=AbstractPlus], amyloidotic vitreous opacities, carpal tunnel syndrome [http://www.ncbi.nlm.nih.gov/pubmed/10403814?dopt=AbstractPlus] and others. In old age, non‐mutated TTR can also form pathological amyloid fibrils [http://www.ncbi.nlm.nih.gov/pubmed/7016817?dopt=AbstractPlus]. Pharmacological intervention to reduce or prevent TTR dissociation is being pursued as a theapeutic strategy. To date one small molecule kinetic stabilising molecule (http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=8378) has been approved for FAP, and is being evaluated in clinical trials for other TTR amyloidoses.Transthyretin (TTR) is a homo‐tetrameric protein which transports thyroxine in the plasma and cerebrospinal fluid and retinol (vitamin A) in the plasma. Many disease causing mutations in the protein have been reported, many of which cause complex dissociation and protein mis‐assembly and deposition of toxic aggregates amyloid fibril formation [et al. (2019) Hereditary transthyretin amyloidosis: a model of medical progress for a fatal disease. Nat Rev Neurol15: 387‐404 [https://www.ncbi.nlm.nih.gov/pubmed/31209302]Adams D et al. (2017) Is transthyretin a good marker of nutritional status? Clin Nutr36: 364‐370 [https://www.ncbi.nlm.nih.gov/pubmed/27381508?dopt=AbstractPlus]Dellière S et al. (2017) Transthyretin amyloidosis: an under‐recognized neuropathy and cardiomyopathy. Clin. Sci.131: 395‐409 [https://www.ncbi.nlm.nih.gov/pubmed/28213611?dopt=AbstractPlus]Galant NJ Biol Pharm Bull41: 979‐984 [https://www.ncbi.nlm.nih.gov/pubmed/29962408]Yokoyama T & Mizuguchi M. (2018) Inhibition of the Amyloidogenesis of Transthyretin by Natural Products and Synthetic Compounds. et al. (2019) Transthyretin Amyloid Cardiomyopathy: JACC State‐of‐the‐Art Review. J Am Coll Cardiol73: 2872‐2891 [https://www.ncbi.nlm.nih.gov/pubmed/31171094]Ruberg FL http://www.guidetopharmacology.org/GRAC/ObjectDisplayForward?objectId=1232) or receptors . Many CDs are targeted for therapeutic gain using antibodies for the treatment of proliferative disorders. A full listing of all the Clusters of Differentiation proteins is not possible in the Guide to PHARMACOLOGY; listed herein are selected members of the family targeted for therapeutic gain.Cluster of differentiation refers to an attempt to catalogue systematically a series of over 300 cell‐surface proteins associated with immunotyping. Many members of the group have identified functions as enzymes ) and programmed cell death 1 ligand 2 . These ligands are cell surface peptides, normally involved in immune system regulation. Expression of PD‐1 by cancer cells induces immune tolerance and evasion of immune system attack. Anti‐PD‐1 monoclonal antibodies are used to induce immune checkpoint blockade as a therapeutic intervention in cancer, effectively re‐establishing immune vigilance. http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=7499 was the first anti‐PD‐1 antibody to be approved by the US FDA.The endogenous ligands for human PD‐1 are programmed cell death 1 ligand 1  The glycobiology of the CD system: a dictionary for translating marker designations into glycan/lectin structure and function. Trends Biochem. Sci.40: 360‐76 [https://www.ncbi.nlm.nih.gov/pubmed/25981696?dopt=AbstractPlus]Gabius HJ et al. (2019) CD markers variations in chronic lymphocytic leukemia: New insights into prognosis. J Cell Physiol. 234: 19420‐39 [https://www.ncbi.nlm.nih.gov/pubmed/31049958]Vosoughi T Methyllysine reader proteins bind to methylated proteins, such as histones, allowing regulation of gene expression.et al. (2018) Histone methylation and acetylation in macrophages as a mechanism for regulation of inflammatory responses. J Cell Physiol. 233: 6495‐9507 [https://www.ncbi.nlm.nih.gov/pubmed/29574768]Daskalaki MG et al. (2019) Epigenetic interplays between DNA demethylation and histone methylation for protecting oncogenesis. J Biochem. 165: 297‐299 [https://www.ncbi.nlm.nih.gov/pubmed/30605533]Furuya K Cell Mol Life Sci76: 2873‐83 [https://www.ncbi.nlm.nih.gov/pubmed/31123776]Levy D. (2019) Lysine methylation signaling of non‐histone proteins in the nucleus. et al. (2019) Understanding histone H3 lysine 36 methylation and its deregulation in disease. Cell Mol Life Sci in press [https://www.ncbi.nlm.nih.gov/pubmed/31147750]Li J et al. (2019) Role of histone modification and DNA methylation in signaling pathways involved in diabetic retinopathy. J Cell Physiol.234: 7839‐7846 [https://www.ncbi.nlm.nih.gov/pubmed/30515789]Shafabakhsh R e.g. in plasma) or transport these agents; to the nucleus to interact with nuclear receptors  or for interaction with metabolic enzymes. Although sequence homology is limited, crystallographic studies suggest conserved 3D structures across the group of binding proteins.Fatty acid‐binding proteins are low molecular weight (100‐130 aa) chaperones for long chain fatty acids, fatty acyl CoA esters, eicosanoids, retinols, retinoic acids and related metabolites and are usually regarded as being responsible for allowing the otherwise hydrophobic ligands to be mobile in aqueous media. These binding proteins may perform functions extracellularly (http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=6735 exhibits high affinity for FABP4 (pIC50 8.8) compared to FABP3 or FABP5 (pIC50 <6.6) . http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=6736 is reported to interfere with FABP4 action [http://www.ncbi.nlm.nih.gov/pubmed/19754198?dopt=AbstractPlus]. Ibuprofen displays some selectivity for FABP4 (pIC50 5.5) relative to FABP3 (pIC50 3.5) and FABP5 (pIC50 3.8) [http://www.ncbi.nlm.nih.gov/pubmed/24248795?dopt=AbstractPlus]. Fenofibric acid displays some selectivity for FABP5 (pIC50 5.5) relative to FABP3 (pIC50 4.5) and FABP4 (pIC50 4.6) [http://www.ncbi.nlm.nih.gov/pubmed/24248795?dopt=AbstractPlus]. Multiple pseudogenes for the FABPs have been identified in the human genome.Although not tested at all FABPs, et al. (2015) Enterocyte fatty acid‐binding proteins (FABPs): different functions of liver and intestinal FABPs in the intestine. Prostaglandins Leukot. Essent. Fatty Acids93: 9‐16 [https://www.ncbi.nlm.nih.gov/pubmed/25458898?dopt=AbstractPlus]Gajda AM Prostaglandins Leukot Essent Fatty Acids93: 45‐9 [https://www.ncbi.nlm.nih.gov/pubmed/25154384?dopt=AbstractPlus]Glatz JF. (2015) Lipids and lipid binding proteins: a perfect match. et al. (2015) Metabolic functions of FABPs–mechanisms and therapeutic implications. Nat Rev Endocrinol11: 592‐605 [https://www.ncbi.nlm.nih.gov/pubmed/26260145?dopt=AbstractPlus]Hotamisligil GS et al. (2016) Fatty acid binding proteins and the nervous system: Their impact on mental conditions. Neurosci. Res.102: 47‐55 [https://www.ncbi.nlm.nih.gov/pubmed/25205626?dopt=AbstractPlus]Matsumata M et al. (2016) Heart lipid droplets and lipid droplet‐binding proteins: Biochemistry, physiology, and pathology. Exp. Cell Res.340: 198‐204 [https://www.ncbi.nlm.nih.gov/pubmed/26524506?dopt=AbstractPlus]Osumi T http://www.ncbi.nlm.nih.gov/pubmed/20971825?dopt=AbstractPlus]. As the Notch ligands are also membrane bound, cells have to be in close proximity for receptorligand interactions to occur. Cleavage of the intracellular domain (ICD) of activated Notch receptors by γ‐secretase is required for downstream signalling and Notch‐induced transcriptional modulation . This is why γ‐secretase inhibitors can be used to downregulate Notch signalling and explains their anticancer action. One such small molecule is http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=7338 [http://www.ncbi.nlm.nih.gov/pubmed/19773430?dopt=AbstractPlus], although development of this compound has been terminated following an unsuccessful Phase II single agent clinical trial in metastatic colorectal cancer [http://www.ncbi.nlm.nih.gov/pubmed/22445247?dopt=AbstractPlus].The canonical Notch signalling pathway has four type I transmembrane Notch receptors (Notch1‐4) and five ligands . Each member of this highly conserved receptor family plays a unique role in cell‐fate determination during embryogenesis, differentiation, tissue patterning, proliferation and cell death , with http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=8451 and http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=8453 identified as antibody inhibitors of ligand:receptor binding [http://www.ncbi.nlm.nih.gov/pubmed/25388163?dopt=AbstractPlus].Aberrant Notch signalling is implicated in a number of human cancers [et al. (2018) Notch signaling and neuronal death in stroke. Prog. Neurobiol.165‐167: 103‐116 [https://www.ncbi.nlm.nih.gov/pubmed/29574014?dopt=AbstractPlus]Arumugam TV et al. (2016) The Notch intracellular domain integrates signals from Wnt, Hedgehog, TGFβ/BMP and hypoxia pathways. Biochim. Biophys. Acta1863: 303‐13 [https://www.ncbi.nlm.nih.gov/pubmed/26592459?dopt=AbstractPlus]Borggrefe T et al. (2015) Ligand‐Independent Mechanisms of Notch Activity. Trends Cell Biol.25: 697‐707 [https://www.ncbi.nlm.nih.gov/pubmed/26437585?dopt=AbstractPlus]Palmer WH et al. (2015) Molecular pathways: translational and therapeutic implications of the Notch signaling pathway in cancer. Clin. Cancer Res.21: 955‐61 [https://www.ncbi.nlm.nih.gov/pubmed/25388163?dopt=AbstractPlus]Previs RA et al. (2015) Targeting Notch, Hedgehog, and Wnt pathways in cancer stem cells: clinical update. Nat Rev Clin Oncol12: 445‐64 [https://www.ncbi.nlm.nih.gov/pubmed/25850553?dopt=AbstractPlus]Takebe N http://www.ncbi.nlm.nih.gov/pubmed/8756726?dopt=AbstractPlus, http://www.ncbi.nlm.nih.gov/pubmed/9108480?dopt=AbstractPlus, http://www.ncbi.nlm.nih.gov/pubmed/9417641?dopt=AbstractPlus], leading to a termination of GPCR signalling. Interactions through protein: protein interactions of many RGS proteins have been identified for targets other than heteromeric G proteins. Sequence analysis of the 20 RGS proteins suggests four families of RGS: RZ, R4, R7 and R12 families. Many of these proteins have been identified to have effects other than through targetting G proteins. Included here is RGS4 for which a number of pharmacological inhibitors have been described.Regulators of G protein signalling (RGS) proteins display a common RGS domain that interacts with the GTP‐bound Gα subunits of heterotrimeric G proteins, enhancing GTP hydrolysis by stabilising the transition state [http://www.ncbi.nlm.nih.gov/pubmed/16765607?dopt=AbstractPlus]. It consists of RGS17 , RGS19  and RGS20 . All members contain an N‐terminal cysteine string motif [http://www.ncbi.nlm.nih.gov/pubmed/17183362?dopt=AbstractPlus] which is a site of palmitoylation and could serve functions in membrane targeting, protein stability or aid protein‐protein interactions [http://www.ncbi.nlm.nih.gov/pubmed/17126529?dopt=AbstractPlus]. However, the function in the case of RZ family RGS proteins is not yet fully understood. Members of the RZ family of RGS proteins are the only RGS proteins that have selective GTPase activating‐protein (GAP) activity for Gαz, a function that resulted in the name of the family . However, the members of the RZ family are able to also GAP Gαi/o members with varying selectivity.The RZ family of RGS proteins is less well characterized than the other families [This is the largest family of RGS proteins.This family of RGS proteins shows some selectivity for Gai/o proteins.http://www.ncbi.nlm.nih.gov/pubmed/26123306?dopt=AbstractPlus]. The Gαi/o‐Loco (GoLoco) motif in RGS12 and 14 has GDI activity (for Guanine nucleotide Dissociation Inhibitor) towards Gαi1, Gαi2 and Gαi3 . Through this activity RGS12 and RGS14 can inhibit G protein signaling both by accelerating GTP hydrolysis and by preventing G protein activation. Splice variants of RGS12 and RGS14 also contain membrane targeting and protein‐protein interaction domains .The R12 family consists of RGS10, 12 and 14. RGS12 and 14 are large proteins with additional domains that can participate in protein‐protein interactions and other functions. In contrast, RGS10 is a small protein consisting of the RGS domain and small N‐ and C‐termini, similar to members of the R4 family. However, sequence homology of the RGS10 RGS domain clearly places it in the R12 family Alqinyah M et al. (2002) Regulators of G‐protein signalling as new central nervous system drug targets. Nat Rev Drug Discov1: 187‐97 [https://www.ncbi.nlm.nih.gov/pubmed/12120503?dopt=AbstractPlus]Neubig RR et al. (2010) Non‐canonical functions of RGS proteins. Cell. Signal.22: 1274‐81 [https://www.ncbi.nlm.nih.gov/pubmed/20363320?dopt=AbstractPlus]Sethakorn N Br. J. Pharmacol.174: 427‐437 [https://www.ncbi.nlm.nih.gov/pubmed/28098342?dopt=AbstractPlus]Sjögren B. (2017) The evolution of regulators of G protein signalling proteins as drug targets ‐ 20 years in the making: IUPHAR Review 21. et al. (2010) Thinking outside of the ‘RGS box’: new approaches to therapeutic targeting of regulators of G protein signaling. Mol. Pharmacol.78: 550‐7 [https://www.ncbi.nlm.nih.gov/pubmed/20664002?dopt=AbstractPlus]Sjögren B http://www.ncbi.nlm.nih.gov/pubmed/27042935?dopt=AbstractPlus] suggests a trimeric structure of a single short transmembrane domain traversing the endoplasmic reticulum membrane, with the bulk of the protein facing the cytosol. A wide range of compounds, ranging from psychoactive agents to antihistamines, have been observed to bind to these sites.Although termed ’receptors’, the evidence for coupling through conventional signalling pathways is lacking. Initially described as a subtype of opioid receptors, there is only a modest pharmacological overlap and no structural convergence with the G protein‐coupled receptors; the crystal structure of the sigma1 receptor [http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=1606 also shows activity at opioid receptors. The sigma2 receptor has recently been reported to be http://www.guidetopharmacology.org/GRAC/ObjectDisplayForward?objectId=2553 [http://www.ncbi.nlm.nih.gov/pubmed/28559337?dopt=AbstractPlus], a 4TM protein partner of NPC1, the Niemann‐Pick C1 protein, a 13TM cholesterol‐binding protein.et al. (2016) Biochemical Pharmacology of the Sigma‐1 Receptor. Mol. Pharmacol.89: 142‐53 [https://www.ncbi.nlm.nih.gov/pubmed/26560551?dopt=AbstractPlus]Chu UB et al. (2015) Sigma‐1 receptor and inflammatory pain. Inflamm. Res.64: 377‐81 [https://www.ncbi.nlm.nih.gov/pubmed/25902777?dopt=AbstractPlus]Gris G et al. 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They are exploited for therapeutic gain in cancer chemotherapy as targets for agents derived from a variety of natural products: taxanes, colchicine and vinca alkaloids. These are thought to act primarily through β‐tubulin, thereby interfering with the normal processes of tubulin polymer formation and disassembly.et al. (2019) Current advances of tubulin inhibitors as dual acting small molecules for cancer therapy. Med Res Rev39: 1398‐1426 [https://www.ncbi.nlm.nih.gov/pubmed/30746734]Arnst KE Proc Natl Acad Sci U S A116: 10366‐10371 [https://www.ncbi.nlm.nih.gov/pubmed/31072936]Eshun‐Wilson L. (2019) Effects of alpha‐tubulin acetylation on microtubule structure and stability. et al. (2017) The tubulin code at a glance. J. Cell. Sci.130: 1347‐1353 [https://www.ncbi.nlm.nih.gov/pubmed/28325758?dopt=AbstractPlus]Gadadhar S et al. (2018) Tubulin Posttranslational Modifications and Emerging Links to Human Disease. 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Chelon haematocheilus) is a cosmopolitan coastal species. It is often consumed as a sliced raw fish in Korea and as a dried and salted fish roe in several countries, including the southeastern United States and Japan. In this study, to optimize traditional processing of salted semidried mullet (SSDM) for the development of high‐quality products, nine different types of traditional process were applied, and quality changes including physicochemical, nutritional, and sanitary properties were observed. The approximate composition of SSDM was as follows: moisture, 66.1% to 71.8%; ash, 1.65% to 3.75%; crude protein, 16.12% to 18.09%; and crude lipid, 1.11% to 2.07%. The salinity, water activity (Aw), color parameters, peroxide value (POV), acid value (AV), thiobarbituric acid (TBA), and the total volatile basic nitrogen (TVB‐N) contents in fresh mullet (FM) and different SSDM groups were affected by different processing techniques including salt concentration and drying methods. In particular, the salinity was significantly increased, whereas the Aw was significantly decreased in all SSDM groups compared to those of FM group. In both FM and SSDM groups, the AV, POV, and TBA values gradually increased with prolonged storage and crude fat content; however, they were not affected by salinity. The amino and fatty acid content also varied depending on the processing method; however, the composition and protein patterns were similar among the groups. The total aerobic bacterial numbers of all SSDM groups were also influenced by different processing methods. The microbial numbers in the mullet after salted semidried treatment were markedly lower than in the FM group during refrigerated storage for 14 days. Therefore, salted semidried treatment for mullet show extended shelf life and improved microbiological safety and biochemical parameters during refrigerated storage.The mullet ( Salted semidried mullet show extended shelf life and improved microbiological safety and biochemical parameters during refrigerated storage. The average body weight and length of fresh mullet were 1.05 ± 0.28 kg and 49.21 ± 2.76 cm, respectively. Blood and other wastes were removed with tap water, and 5 individual fresh mullets per group were selected, and then, the SSDMs were manufactured immediately by nine manufacturers using different salting and drying procedures based on traditional salting and semidry methods and then called “SSDM 1 ~ 9.” As shown in Table Whole fresh mullets  at 27°C. The chromaticity was measured with a color meter  using the muscular part of the SSDM as a sample, and the L* value , a* value , and b* value  were recorded. The L value of the standard white plate of the color difference meter was 97.50; the a and b values were −0.27 and 0.21, respectively. Each group of samples was measured five times, and the mean values were obtained.The moisture, protein, and ash contents of SSDM samples were determined using methods described by the Association of Official Analytical Chemists AOAC, . Moistur2.3v/v) and 1 ml of saturated potassium iodide. The mixture was stored in the dark for about 10 min and then added a 30 ml of distilled water and 1 ml of 1% starch (w/v) solution. The sample was titrated with 0.01 N sodium thiosulfate until the blue color disappeared. The PVs were expressed as milliequivalents of peroxide oxygen per kg of sample (mEq/kg). The lipid peroxidation was evaluated by measuring TBA levels using the modified method of Faustman, Specht, and Malkus  equivalent/kg of sample.Lipid oxidation of SSDM samples was assessed according to the acid value (AV), peroxide value (PV), and the thiobarbituric acid (TBA) levels. The AV was determined using the procedure described by Pearson . Brieflyd Malkus . A 20 g 2.4Amino nitrogen content was evaluated using the formol titration method  and then distilled with a Kjeldahl nitrogen apparatus . The distillate was obtained with 20 ml of boric acid (0.02 g/L) containing methyl red (1 g/L) and methylene blue (1 g/L) in ethanol as a mixed indicator. The mixed solution was titrated using 0.01 mol/L HCl solution, and 5 ml of distilled water was used instead of the sample as a blank test. The TVB‐N value was calculated based on the consumption of HCl according to the following equation:V1 and V2 are volume (mL) of HCl used for the sample and the blank, respectively. C refers to the concentration of HCl (mol/L). m indicates the sample weight (g).The TVB‐N was determined via the microtitration method described by Gharibzahedi and Mohammadnabi . Briefly2.6TM‐2560, 100 m × 0.25 mm i.d, 0.25‐μm film thickness, Supelco). Fatty acid analysis was carried out using an initial isothermic period of 140°C for 10 min, followed by a temperature increase at the rate of 4°C/min to 240°C and an isothermic period of 240°C for 30 min. FAMEs n‐hexane (1 μl) was injected into the column. The injection and detector port were maintained at 260°C, with helium gas. The compositions of fatty acid were identified by comparing the retention times of FAME peaks with the standard  and then quantified as mg per kg of SSDM samples using the internal standard. The total fatty acid content was expressed as g per 100 g of samples, while individual fatty acid composition was expressed as a weight percentage of the total fatty acids.To analyze the fatty acid, total lipids obtained from the SSDM samples were extracted using a mixture of chloroform:methanol  including 0.01% butylated hydroxytoluene. The extracted lipids were dried using a rotary evaporator  in vacuum and then converted to fatty acid methyl esters (FAMEs) through base‐catalyzed transesterification with sodium methoxide for 2 hr at 30°C . Samples were filtered using a syringe filter (0.45 μm) and then analyzed amino acids by reaction with ninhydrin using Biochrom 20 amino acid analyzer (Pharmacia Biotech). Amino acid composition was determined by measuring absorbance at 440 and 570 nm, respectively.To analyze the amino acid, 80 mg of SSDM samples was mixed with 10 ml of 6 N HCl solution. After purging with N2.8g for 30 min to separate the supernatant. Protein in the supernatant was quantified, mixed with sample buffer, then heated at 100°C for 5 min, and used for SDS‐PAGE analysis. Electrophoresis was conducted using a Mini‐PROTEAN Tetra Cell  according to the method of Laemmli  and homogenized with 100 ml physiological saline (0.85%) for 2 min. The pretreated samples were cultured in 3M™ Petrifilm™ Plates (3M Microbiology Products) at 35 ± 1°C for 48 hr, and then, the number of red colonies was counted. The average number of colonies was multiplied by the dilution factor. All counts were expressed as log10 cfu/g.Microbiological analyses were conducted using a commercially available 3M™ Petrifilm™ Plates (3M Microbiology Products), according to the methods suggested by the manufacturer. Briefly, The SSDM samples (10 g) were placed in a sterilized pack (3M2.10TM Sample Bag) supplemented with 0.9% (v/w) of 0.85% physiological saline and homogenized for 2 min. The sample suspension (1 ml) was cultured in 3M dry petrical medium (3M Microbiology Products) and incubated at 35 ± 1°C for 24 hr. Red colonies surrounded with trapped gas represented coliforms, whereas blue colonies with trapped gas were identified as E. coli. Each dilution was conducted in duplicate, and plates containing 15–150 colonies were recommended for counting. The colony‐forming unit (CFU) per gram of sample was used, and the minimum limit for detection was log cfu/g.Microbiological analyses were conducted using a commercially available 3M™ Petrifilm™ E. coli/Coliform Count Plate (3M Microbiology Products), according to the methods suggested by the manufacturer. SSDM samples (10 g) were placed in a sterilized pack  is closely related to lipid oxidation of fish flesh  in the L, a*, and b* values of the groups (fresh and SSDM samples) with the different salting or processing methods. In this study, the average values of redness (a*) were in the range of −1.34–2.43, and those of yellowness (b*) were in the range of 6.84–12.27. In particular, L and b* values of SSDM samples were significantly increased except in SSDM1 group compared with those of the fresh mullet samples. These results may be attributed to the soaked salting and drying process in SSDM groups. Çelik et al.  similar to our study. Köse, Koral, Özoğul, and Tufan (The compositions of fatty acids (FAs) of SSDM are summarized in Table nd Tufan  also repnd Tufan  reported3.6The constituent amino acids of fresh and SSDM are shown in Table 4The muscle fiber protein of fish meat generally constitutes 60%–70% of the muscle protein. It contributes to the physical properties of dietary protein as well as playing a role in muscle tissue formation as a structural protein. It has been known that the reactivity of the proteolytic enzyme to the myofibrillar protein depends on the freshness and quality of fish    after 14 days of refrigerated storage compared to levels of 7.76 log cfu/g (increasing rate: 2.6 log cfu/g) in SSDM4, 8.41 log cfu/g (increasing rate: 3.1 log cfu/g) in SSDM9, 7.38 log cfu/g (increasing rate: 3.4 log cfu/g) in SSDM5, and 7.69 log cfu/g (increasing rate: log cfu/g) in SSDM1, respectively. Similar to our results, Siriskar et al. (2 log CFU/g, which increased up to 6.4 × 103 log CFU/g during 5 weeks of storage. In our study, the rapid increase in total microbial counts during storage of FM group may be attributed to the high moisture content, Aw, and low salinity compared with those of the SSDM groups.Table r et al.  reported5This study represents the first report of physicochemical, nutritional, and sanitary properties of SSDM produced with different pretreatment methods including salting and drying at refrigerated temperatures. The different pretreatment techniques affected the TVB‐N content and lipid oxidation parameters such as POV, AV, and TBA and TBARS. Compared with the increasing microbial levels in FM group during storage, the SSDM groups showed a decrease in microbial content. Our findings suggested that the pretreatment method was one of the important factors in determining the physicochemical and nutritional properties, and the hygienic quality of SSDM products during refrigerated storage. In the present study, we confirmed that the SSDM produced by traditional methods improved the storage period significantly, unlike the fresh mullet. However, there is a need to simplify and standardize the traditional manufacturing methods and conditions to produce efficient salted semidried fish products.The authors declare that they do not have any conflict of interest.This study does not involve any human testing.


To review the risk factors and pathogenesis of endothelial decompensation after penetrating keratoplasty (PKP) and its novel therapeutic strategies.  Literature review.  As the major cause of graft failure in PKP, endothelial decompensation of corneal allograft is considered an irreversible decrease in endothelial cell density and endothelial dysfunction. Various risk factors, including donor status and operative and recipient factors, have been found to be associated with this pathological process. Operative factors like graft size and recipient factors such as indications, glaucoma, or glaucoma surgery history are highly associated with the occurrence of endothelial decompensation, while others are still under investigation. Although the mechanism of these risk factors remains unclear, pathogenesis can be summarized as an acute and chronic loss of endothelium, and cell exchange between donor and recipient is at the core of chronic cell loss. Endothelial keratoplasty has been a useful alternative to repeat standard PKP in eyes with failed grafts. Descemet stripping automated endothelial keratoplasty (DSAEK) and Descemet's membrane endothelial keratoplasty (DMEK) following failed PKP provide more rapid visual recovery and achieve better rates of graft survival than those of a second PKP.  Any direct or indirect damage to the endothelium could cause the loss, morphological changes, and dysfunction of endothelial cells. Graft size, indications, and recipient glaucoma or glaucoma surgery history are risk factors for endothelial decompensation. DSAEK and DMEK are novel therapeutic strategies for failed PKP grafts and have potential superiorities compared with repeat PKP. For more than half a century, penetrating keratoplasty (PKP) has been the most common allograft surgery and caters successfully to most causes of corneal blindness, including stromal or endothelial disease. Notwithstanding the rapid progression of newer keratoplasty procedures, PKP is still frequently employed worldwide . The 10-Endothelial cells lack the capacity to reproduce; any direct or indirect damage to transplanted corneal endothelial cells during or after PKP would lead to the depletion of these cells. Since the normal function of endothelial cells is crucial for the maintenance of corneal transparency, the accumulative loss of endothelial cells might finally reach a minimum threshold, followed by functional decompensation resulting in corneal edema and opacity. This irreversible reduction in endothelial cell density (ECD) and endothelial dysfunction of the corneal graft is defined as graft endothelial decompensation . For decThe patient who experiences endothelial decompensation of the PKP graft desires a second graft. Previously, all patients with endothelial failure received a repeat PKP for treatment. Unfortunately, after a repeat PKP, the patient is once again subjected to prolonged visual recovery, unpredictable refractive results, risk for suture-related complications, and an unstable full-thickness wound. Even more detrimental is that PKP has a much poorer prognosis for survival than initial keratoplasty . With reIn this review, we analyze the changes in the corneal endothelium after PKP and summarize risk factors for endothelial decompensation after PKP, which are classified as donor status and operative and recipient factors, as well as the pathogenesis. The novel therapeutic strategies that are used to treat failed PKP grafts, such as DSAEK and DMEK, have been validated in recent research. We also compare graft survival, visual recovery, and the occurrence of related complications, such as graft dislocation and graft rejection, among DSAEK, DMEK, and repeat PKP.Owing to the two properties of corneal endothelial cells, their function as a sodium pump to maintain transparency, and their lack of regeneration ability, the long-term optical clarity of the cornea after PKP is decided by the number, morphology, and function of donor endothelial cells . However2 [2 [2 [2 in their cohort of post-PKP patients [According to previous studies, the density of endothelial cells after the first ten years following PKP has been reported to be 960 ± 470 , 840 ± 12 , and aft2  or 666 ±2 [2  .2 [2 . Between2 [2 . Additio2 [2 . This ra2 [2 [2 , functio0 − (t ∗ CL), where ECD0 represents the preoperative ECD, t is the postoperative time point in years, and CL means the annual rate of endothelial cell loss [In recent decades, several models have been proposed to explain how ECD changes over time. The linear model assumes a constant and endothelial cell loss with time: ECD = ECDell loss , 33. In ell loss . The firell loss , 23, 34.Endothelial cells are markedly enlarged in long-term corneal allografts, and other morphological alternations are an increased coefficient of variation (CV) of the cell area and decreased percentage of hexagonal cells (HEX) . HoweverHowever, morphological alternations also provide a basis for endothelial dysfunction. As is commonly acknowledged, the deturgescence and clarity of the cornea depends on the pump-leak mechanism of monolayer cells lining the inner surface. The so-called pump-leak mechanism explains the two functions of the corneal endothelium, maintaining stromal deturgescence and clarity by actively pumping out fluid and forming a leaky barrier that enables fluid to leak back into the stroma. Even if their number is decreased by 80%, the function of the corneal endothelium can still be sustained . NeverthIn the ACGR 2012 Report, endothelial decompensation accounted for 15% of all causes of graft failure . Thus, i2, and ECD is known to decline with age [Endothelial failure in corneal grafts is associated with ECD in the range from 250 to 500 cells/mmwith age . Thus, iwith age , 14. In with age . Howeverwith age . Howeverwith age . SMAS rewith age . Althoug2 on endothelial failure at 5 years after PKP [2. These data seem to be in agreement with the corneal donation policy of no upper age limit in the UK, or under 75 years of age in the US, if a lower limit of donor ECD is applied [Most recently, Wakefield et al. performed a large study including a total of 9415 patients after their first PKP . They refter PKP . It appe applied . FurtherMany studies conducted in animals and investigating imaging, function, or cataract surgery have shown that diabetes mellitus may have harmful biochemical , morpholA larger graft size following PKP has been associated with less endothelial cell loss in bullous keratopathy and Fuchs dystrophy . The stuIn addition to the graft characteristics, other possible surgical factors that influence endothelial cell loss are under discussion. In early assessments, organ culture conditions for transplant preservation were considered to cause additional endothelial cell loss. However, recent studies have illustrated the absence of statistically significant differences in postoperative rates of endothelial cell loss between corneas stored in tissue culture medium and organ-cultured corneas , though Bullous keratopathy, Fuchs dystrophy, keratoconus, and corneal scarring are considered main indications for PKP . PatientAs relatively uncommon indications for PKP, corneal trauma and chemical and thermal burns lead to a high incidence of endothelial decompensation due to the complexity of the surgeries and lack of integrity of the eyeball. The appearance of decompensation also occurs earlier because of the serious damage and high incidence of early complications , 53. RegFor leucoma, fungal keratitis, and herpes simplex keratitis, PKP is relatively safe from endothelial decompensation . For funFor decades, the relationship between glaucoma and endothelial decompensation has been a hotspot in the field of corneal transplantation. Experimental studies have demonstrated a relationship between elevated IOP and endothelial cell loss in animal models, and a clinical study in glaucoma patients with healthy corneas showed that the patients had a significantly lower ECD compared with a control group with normal IOP , 55. RegFor IOP-related endothelial cell damage, no definite explanation has emerged to date. The pressure-induced induction of apoptosis in corneal endothelial cells may provide a possible explanation . AdequatEvidence supports that an acute loss of donor endothelium at the time of surgery results from a combination of surgical or corneal harvest trauma, and preservation damage. After keratoplasty, there is a greater rate of cell loss than the normal aging process. In all the endothelial decompensation cases that occurred more than 5 years postoperatively, 44.4% had acute rejection reaction once . BecauseHowever, even if the acute rejection can be controlled by medicine and the graft has restored transparency, loss of endothelial cells can still occur. Researchers have also observed that while 27.8% of cases show no significant clinical features indicative of rejection and the grafts remain transparent after PKP , after sCell exchange between donor and recipient also appears to influence the rate of endothelial cell loss . The humHowever, the role of immunologic factors remains controversial, and some studies have shown that these chronic processes occur in the absence of rejection since immune effector cells have not been found , 16, whiIn summary, at the time of surgery, surgical trauma and preservation damage account for the acute loss of donor endothelium. Postoperatively, acute rejection reactions play a role in endothelial cell loss. Apart from the effect of aging, the progressive chronic cell loss for years, which finally leads to late endothelial failure, can be mainly interpreted as cell exchange between donor and recipient. The role of chronic subclinical immune reactions is also a possible mechanism. The risk factors discussed above, such as donor age, graft size, and elevated IOP  in recipAs is described above, multiple factors have been associated with the endothelial failure of penetrating keratoplasty . PreviouBy avoiding new disruptions of the corneal architecture and previous surgical scars, DSAEK represents a less-invasive procedure in comparison to repeat PKP . PreviouCovert and Koenig reported a prospective surgical case series of 7 eyes of 7 consecutive patients undergoing DSAEK for graft failure after PKP . Except Risk factors for graft failure in DSAEK after failed PKP have also started to become a focus of many researchers. Straiko et al. recommended that an oversized DSAEK graft could negatively affect its long-term survival . HoweverIn 2006, Price and Price first reported that six out of seven patients undergoing endothelial keratoplasty after PKP experienced an improvement in visual acuity (VA) . LikewisThe most frequent endothelial keratoplasty complication is early graft detachment either performed as a primary procedure or regraft . TherefoFactors contributing to the graft detachment have been discussed in numerous studies. The optimal sizing of the donor DSAEK grafts has been conflicting. Straiko et al. analyzed 17 eyes undergoing DSAEK after PKP and concluded that the use of smaller and equal DSAEK grafts could allow improved vision with a low rate of graft detachment . HoweverOther than graft dislocation, few detail additional complications, such as graft rejection, elevated postoperative IOP, infection, or epithelial ingrowth, have been reported. Jangi et al. reported a graft rejection rate of 3.5%, with no cases of infection or epithelial downgrowth . HoweverRecently, Descemet's membrane endothelial keratoplasty (DMEK) has revolutionized the treatment of endothelial dysfunction, and thanks to excellent clinical results, indications for DMEK have been extended . So far,In 2013, Anshu et al. first reviewed 4 patients with failed PKP who were managed with DMEK surgery and reported that the patients showed improvements in vision with a median BCVA of 20/50 as early as 1 month postoperatively . GundlacWith avoidance of full-thickness incisions and multiple sutures on the cornea, DMEK offers great advantages over repeat PKP similar to those of DSAEK. Gundlach et al. also observed more benefits with DMEK than repeat PKP, including fewer postoperative complications associated with the suture, stable refraction, a lower rejection rate, and a shorter duration of local steroid therapy . HeinzelThere are still limitations of DMEK compared with conventional PKP or even DSAEK, such as difficulty associated with the donor graft preparation and the achievement of complete graft attachment. Fortunately, recent technique improvements have reduced the occurrence of tissue loss and dramatically improved graft attachment rates. With the advantages of rapid visual recovery and fewer complications, this newer EK technique is still very attractive, especially for patients who are longing for rapid visual rehabilitation or at an increased risk for graft rejection. However, due to the relatively small sample sizes and heterogeneous nature of current research, further studies are warranted to verify these points and identify pre- and postoperative risk factors associated with outcomes.Recently, several observational studies have compared the outcomes of endothelial keratoplasty (EK) after a previously failed PKP with repeat PKP, although inconsistent results have been reported. Keane et al. collected data on 400 eyes with a second graft after a failed PKP that was performed initially for keratoconus or pseudophakic bullous keratopathy (PBK). The authors suggested that repeat PKP might deliver a better outcome than EK after failed PKP in terms of graft survival, but visual outcomes appeared to be equivalent across groups for the surviving graft . In contThus, a meta-analysis was performed to compare graft survival, graft rejection, and the visual outcome of EK with repeat PKP after failed PKP, which included above-mentioned studies . HoweverAlthough these results were limited and inconclusive due to their small sizes and heterogeneity, the findings indicated that EK might be a better alternative to repeat PKP for second corneal transplantation with a lower graft rejection rate, especially for patients with prior graft failure resulting from endothelial edema or rejection. Further comparative studies with a larger size, longer follow-up, and well-described visual acuity outcome measurements are needed to improve our understanding of the benefits of EK versus repeat PKP for the treatment of failed PKP.Any direct or indirect damage to the endothelium could cause the loss, morphological changes, and dysfunction of endothelial cells. Graft size and recipient factors such as indications, glaucoma, and glaucoma surgery are all highly associated with the occurrence of endothelial decompensation, while others are still under investigation. The pathogenesis can be concluded to be an acute and chronic loss of endothelium, and cell exchange between donor and recipient is at the core of chronic cell loss. DSAEK and DMEK are novel therapeutic strategies for failed PKP grafts and have potential superiorities compared with repeat PKP.


Pasting properties of barley starch are important characteristics from a processing standpoint. The isolation of starch form barley grains is time consuming thus the whole grain flour is always used. To compare pasting properties of starch with those of the whole grain flour, we used a Rapid Visco Analyser (RVA) to measure pasting properties of three types of samples: grain flour and starches isolated using two different extraction methods. We also investigated compositional, morphological and structural properties of the two starch samples. Significant differences in pasting properties were found among the three sample types, but most of the parameters of pasting properties displayed significant correlations between flour and starch. No significant differences were found in amylose/amylopectin ratio, granule morphology, granule size distribution and crystal structure between starches extracted using two different methods. However, the starch isolated from water homogenization had a higher protein content and lower total starch, amylose and amylopectin contents than the starch extracted with homogenized extraction under alkaline conditions. We concluded that the whole grain flour can be used to predict the pasting properties in breeding programs. The functionality and quality of starchy cereal-based products mainly depend on starch properties and characteristics . The pasSeveral different methods have been used for starch pasting analysis. These include Rapid Visco Analyser (RVA), rheometer and amylograph. Of these, RVA is the most commonly used method in the viscosity measurement, primarily because of its advantages in fast determination and the smaller sample sizes required . In the Given that starch isolation is expensive and time consuming, can whole grain flour be used to predict starch pasting properties? The purpose of this study is to compare pasting properties of barley grain flour and extracted starches using two different methods. The results will provide a useful reference to researchers in selecting quality traits.Hordeum vulgare L.) varieties were used in this study. Of them, Yangnongpi7 (YNP7) and Yangnongpi11 (YNP11) were hulled barley, while Emai507 (EM507) and Huangchangmang (HCM) were hull-less barley. In addition, the pasting properties of other thirty hulled barley varieties were also measured using RVA  was adopted as described by Li et al.  with sliRVA  was used in this study. 4.0 g flour or 3.0 g starch was directly weighed into an RVA canister, followed by the addition of 25 g distilled water. The starch slurry was heated from 50°C to 95°C at the rate of 12°C/min, maintained at 95°C for 2.5 min, and then cooled to 50°C at the same rate. Paddle speed was set at 160 rpm . Paramet™ 2300  according to the Kjeldahl method [The total starch content, amylose content, amylopectin content and the ratio of amylose/amylopectin were determined by using Total Starch Assay Kit  together with AM/AP assay Kit . The protein content was measured by using FOSS Kjeltec l method  and the The starch was pretreated and then viewed with an environmental scanning electron microscope (SEM) (Philips XL-30) according to the method of Fan et al. .The particle size of the starch was analysed by a laser diffraction particle size analyser  according to the method of Fan et al. . The staOrdered structure of starch external region was analysed on a Varian 7000 Fourier transform infrared (FTIR) spectrometer with a deuterated triglycine sulphate detector equipped with an attenuated total reflectance (ATR) single reflectance cell containing a germanium crystal (45° incidence angle)  as previously described by Cai et al. .Crystal structure of starch was analyzed by X-ray diffraction (XRD) . The pretreatment of starch samples, XRD analysis and relative crystalline degree (%) analysis were performed by the method described by Fan et al. . The relAnalysis of variance (ANOVA), multiple comparison, t-test and correlation analysis as well as descriptive statistical analysis were all conducted with SPSS statistical software Version 16.0.The pasting properties of the three different samples from four barley varieties as analyzed by RVA are shown in The data on composition properties of grain flour and the two starch samples from four barley varieties is presented in Scanning electron microscopy (SEM) images of starch granules isolated by two methods from four barley varieties are shown in −1 of starch are summarized in The ratios of 1045/1022 and 1022/995 cmRVA has been widely used to determine starch pasting properties . In barlOther components in starch can influence the RVA analysis , 7–10, hIt is well known that lipid and soluble sugar can be removed by steeping and washing with anhydrous ethanol . SignifiIn conclusion, significant correlation was found between RVA measurements of grain flour and starch. Considering that grain flour is easier to be obtained, when a large number of samples need to be tested in breeding programs, the whole grain flour can be used. Barley grain starch isolated with 0.2% NaOH showed no changes in structural properties and is suggested to be used in studying starch properties.S1 FigI, the sample of starch isolated from method 1; II, the sample of starch isolated from method 2.(TIF)Click here for additional data file.S2 FigA: YNP7; B: YNP11; C: HCM; D: EM507. I, the sample of starch isolated from method 1; II, the sample of starch isolated from method 2.(JPG)Click here for additional data file.S3 FigA: YNP7; B: YNP11; C: HCM; D: EM507. I, the sample of starch isolated from method 1; II, the sample of starch isolated from method 2.(JPG)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.


The main and corresponding author, “Mohammad Tasyriq Che Omar” submitted this article to the “Advanced Pharmaceutical Bulletin” Journal on 20 of April 2017 and it was published after positive reviews in: Adv Pharm Bull, 2017, 7(2), 299-312, doi: 10.15171/apb.2017.036.Recently we were informed by an email that this work was carried out under direct supervision of a researcher in the “Advanced Medical and Dental Institute, Universiti Sains Malaysia” between 2013-2016. On the submitted and published manuscript “Mohammad Tasyriq Che Omar” did not include the name of his supervisor as an author, who substantially contributed to conception and design of the work. No permission was obtained from the supervisor for submission of this work.We contacted “Mohammad Tasyriq Che Omar” regarding this issue and he admitted this mistake. He requested to add his supervisor’s name on the published paper. This could not be happened as it is against the current regulations and professional ethics.Publication of this work without the knowledge, consent, and permission of the PhD supervisor and without his name is unacceptable and reflective of extremely poor professional ethics. The editors of the “Advanced Pharmaceutical Bulletin” Journal who act according to the COPE Code of Conduct, consider this an infringement of professional ethics and the decision has been made to retract the article published in the Journal.The editors of “Advanced Pharmaceutical Bulletin” Journal are sorry for any inconveniences caused to the reviewers, editorial staff and to the readers.Prof Hadi Valizadeh“Advanced Pharmaceutical Bulletin” Editor-in-Chief