Among these, neprilysin generates C-terminally modified Ang fragments, releasing Ang-(1-7) from both Ang I and Ang-(1-9) [28]. A variety of enzymes displaying CPA-like activity have also been implicated in the proteolytic processing of Ang peptides. Cathepsin A of human heart generates Ang-(1-7) and Ang-(1-9), two molecules that act as bradykinin potentiator and ACE inhibitor, respectively [12]. Besides, in the human heart a selleck chemicals mast cell CPA-like enzyme has been proposed to regulate the local Ang II formation by releasing the ACE inhibitor Ang-(1-9) into the interstitial fluid [13]. In porcine kidney, cathepsin

A seems to participate in the local RAS by forming Ang-(1-9) and Ang II, but not Ang-(1-7) [19]. The identification of ACE2 by genomic approaches as a human homolog of ACE that displays carboxypeptidase activity [6] and [30] reinforces

the current awareness of the functional complexity of the multifaceted, multicomponent RAS. ACE2 can act upon Ang I and Ang II to generate Ang-(1-9) and Ang-(1-7), respectively, two metabolites that oppose the action of Ang II either by regulating the formation of Ang II PD-1/PD-L1 tumor by ACE [13] and [29] or triggering opposing biological responses mediated by distinct receptors [7]. In previous investigations we showed that the perfused ex vivo preparation of the rat mesenteric arterial bed (MAB), known as the McGregor’s preparation [18], secretes a multiplicity of Ang I- and Ang II-processing CPs potentially relevant to the metabolism of vasoactive and other peptides in the rat mesentery [22] and [25]. To further characterize these enzymes, in the present study we aimed at: (1) identifying the CPs that Orotidine 5′-phosphate decarboxylase constitute major Ang processing pathways in the rat MAB perfusate; (2) investigating the enzymatic activities of purified CPs obtained from rat MAB perfusate toward Ang I, Ang-(1-9), Ang II and Ang-(1-12); and (3) determining the expression profile

of the mRNAs for the different CPAs in representative rat tissues, in which RAS is believed to play a functional role in the local circulatory system. Potato carboxypeptidase inhibitor (PCI), N-carbobenzyloxy-Val-Phe (Z-Val-Phe), Ang I (Asp1-Arg-Val-Tyr-Ile-His-Pro-Phe-His-Leu10), Ang II (Asp1-Arg-Val-Tyr-Ile-His-Pro-Phe8), bradykinin (BK; Arg1-Pro-Pro-Gly-Phe-Ser-Pro-Phe-Arg9), dl-2-mercaptomethyl-3-guanidinoethylthiopropanoic acid (MGTA),1,10-phenanthroline, soybean trypsin inhibitor (SBTI) and DEAE-Sepharose fast flow were obtained from Sigma Chemical Co. (St. Louis, MO). Ang-(1-9) and Ang-(1-12) were synthesized by conventional Fmoc solid phase peptide synthesis [8] and purified by C-18 reversed-phase HPLC. Packed MonoQ 5/5 column was from Pharmacia Fine Chemicals (Uppsala, Sweden). All other reagents used were of analytical grade. All animal protocols were approved by the School of Medicine of Ribeirão Preto Institutional Animal Care and Use Committees.

(1986). The

result of the fitting is shown in Figure 3. Here we see that the quadratic form has a higher coefficient of determination. The quadratic function has a zero for U ≈ 2.7, whereas function f(U3.41) has a zero for the negative value of the domain and intersect with the see more OY axis in f(u3.41 = 0) = 1.2 × 106, which is why applying f(U2) is more realistic. The next argument in favour of using the quadratic dependence is the quadratic relation between aerosol optical depth (AOD) and wind speed with a strong correlation (r2 ~ 0.97), as reported by Mulcahy et al. (2008) for clean marine conditions.In the following we will use the quadratic function. The flux values presented in Figure 3, confirm the usefulness of the quadratic function for the fit. In this case as the first part of SSGF we propose: equation(5) f1(U)=41496×U2−307140.f1(U)=41496×U2−307140. The next step in calculating SSGF is to find the dependence of the flux on the particle radius. In order to obtain function f2(r) the method suggested by Petelski & Piskozub (2006) was applied. The fluxes were classified into ten different wind speed ranges. Each series from the range of U – 0.5 ms−1 to U + 0.5 m s−1 was assigned to an integer wind speed U class. Figure 4 shows four examples selleck chemicals for wind speeds of 8, 10, 13 and 17 m s−1. In order to find the

f2(r) equation for each class, a linear approximation in the ln(f2), 2r space was used. For each wind speed the following function was fitted: equation(6) ln [f2(r)]=a2r+b,ln [f2(r)]=a2r+b,where f2(r) = exp(a2r + b), a and b are fitting coefficients. For each wind class there is one pair of coefficients. In the subsequent calculations the average value of coefficient

a was used (a = –0.62 μm). Factor b increases with wind speed, and this increase can be approximated with a linear function, although the results are rather scattered. In this case we have to change our approach. Data for the total fluxes of aerosol particles are statistically more reliable than each flux for one diameter range separately. Thus, instead of a linear function b(U), we used a first-order fit of function (AU2 + B): equation(7) AU2+B=∫rmin∞exp(−a2r+b)dr,where many rmin = 0.25 μm is the radius of the smallest particle that is measureable with the instrument used in the study. From equation (6) one can obtain: equation(8) exp(b)=[AU2+B]/[−2aexp(a2rmin)].exp(b)=[AU2+B]/[−2aexp(a2rmin)]. In this equation b is present as a function of wind speed. Using equation (8) in the exponential form of function f2 in equation (6), we can derive a new form of the SSGF in which equation(9) f1(U)=AU2+B,f2(r)=(−1/2a)exp[2a(r−rmin)],where A = 41496 s m−4, B = –307140 1/m2 s. Hence, the function we are looking for is equation(10) F(U,r)=f1(U)f2(r)=(−κ/2a)×(AU2+B)×exp[a2(r−rmin)].F(U,r)=f1(U)f2(r)=(−κ/2a)×(AU2+B)×exp[a2(r−rmin)].This function is valid for U ≥ 3 ms−1.

Even though tracking and collection of data through devices on marine animals that have transited or at least partially inhabit a coastal state׳s territorial sea and EEZ might appear to implicate the sovereignty and jurisdiction of the coastal state, it does not because the marine species are autonomous and entirely

Pirfenidone manufacturer independent of any human programming or control. Coastal states have authority over marine scientific research (MSR) that is conducted in their territorial sea and exclusive economic zone (EEZ). Traditionally, MSR was done from a ship operating in the EEZ, and the presence of the ship in water under the sovereignty or jurisdiction of the coastal state required the consent of the coastal State. Bio-logging, however, is a new form of MSR that is not similarly constrained. Bio-logging permits the collection and use of data transmitted or retrieved from devices check details affixed to marine animals [2]. When the devices are attached to marine migratory species on the high seas or in any other area outside of the jurisdiction of a particular coastal state, and the animals subsequently migrate into the territorial sea or exclusive economic zone (EEZ)

of that state, it is not entitled to require permission or withhold consent for the MSR even though the data were collected in areas under its sovereignty

or jurisdiction. Coastal states enjoy sovereignty over the territorial sea, although their authority is not unlimited. Ships of all states, for example, may exercise the right of innocent passage, and entry into the territorial sea in case of force majeure is lawful as well. Likewise, coastal states have sovereign rights and jurisdiction over the living and non-living resources in the EEZ, as well as jurisdiction over some types of vessel-source pollution. Similarly, in the EEZ, although the coastal state enjoys exclusive sovereign rights Quisqualic acid “for the purpose of exploring and exploiting, conserving and managing” marine species, they do not claim exclusive ownership over migratory species, such as sea turtles, “at least not while they are swimming freely in their natural habitat – the oceans.” 2 Furthermore, coastal states are presumed to authorize their consent for marine scientific research (MSR) in their EEZ, although they are entitled to withhold consent under some circumstances. Bio-logging and tracking of marine migratory species is a form of MSR, however, that bypasses the traditional method of marine science conducted from a dedicated research vessel, thereby complicating (or even erasing) the coastal state׳s exclusive authority to control it.

, 2005 and Dobelle, 2000). The attractiveness of visual cortex as the stimulation site for a visual prosthesis

is based on several factors. Firstly the large surface area of visual cortex and the cortical magnification SB431542 price factor combine to render it more amenable to implanting large numbers of electrodes in cortical areas subserving central vision (Daniel and Whitteridge, 1961 and Harvey and Dumoulin, 2011), potentially offering a higher-resolution visual experience than either LGN or retinal implants. Secondly, the stereotactic implantation of small occipital cortical electrode arrays is a relatively straightforward procedure compared to implanting deep LGN electrodes or microarrays onto, or under the retina. Lastly, the utility of direct cortical stimulation extends to all causes of visual impairment in

patients with late blindness due to retinal or optic nerve disease or injury. Cortical visual prosthesis research therefore has enormous PD-1/PD-L1 tumor potential for future treatment of visual impairment, and three research groups known to us report ongoing plans, either in the scientific literature or via their institutional websites, to develop a cortical visual prosthesis (Table 1). Many other research groups are conducting research within the general domain of neural prosthetics, much of which may translate to a cortical visual prosthesis. A number of these studies are covered throughout this review. Visual cortex electrical stimulation has a rich history spanning almost a century, beginning with the early 20th century observations of Löwenstein and Borchardt (1918), who stimulated the occipital cortex of soldiers with occipital bullet wounds. Research involving

such patients provided a wealth of data, with Krause and Förster subsequently demonstrating that stable, punctate phosphenes could be elicited by electrical stimulation of occipital cortex (Förster, 1929, Krause, 1924 and Krause oxyclozanide and Schum, 1931). These studies also confirmed that the retinotopic map of visual cortex was roughly equivalent to that proposed by Inouye and Holmes, who examined visual field defects of soldiers with occipital bullet wounds and concluded that the occipital pole subserved central vision (Glickstein and Whitteridge, 1987 and Holmes and Lister, 1916). After Penfield׳s extensive mapping studies (Penfield, 1947) and Button and Putnam׳s rudimentary but groundbreaking attempts to provide visual perception to four blind volunteers (Button and Putnam, 1962 and Button, 1958), the first attempt to produce a genuinely functional visual prosthesis was made by Brindley and Lewin (1968). Their implant was a significant advance on Button and Putnam׳s four stainless steel wires, consisting of an array of eighty 1 mm2 platinum electrodes embedded in a silicon substrate and molded to the recipient׳s occipital cortex.

, 2011). Several studies have demonstrated that astaxanthin exhibits a wide variety of biological

activities, including the prevention and treatment of various diseases, such as cancers, chronic inflammatory diseases, metabolic syndrome, diabetes, diabetic nephropathy, cardiovascular diseases, gastrointestinal diseases, liver diseases, and neurodegenerative diseases (Chew et al., 1999, Jyonouchi et al., 2000, Kishimoto et al., 2010, Marin et al., 2011, Naguib, 2000 and Otton PR-171 in vitro et al., 2011). The presence of the hydroxyl and keto moieties on each ionone ring (Fig. 1) explains some of its unique features such as the ability to be esterified, a higher antioxidant activity, and a more polar nature than Proteasome inhibitor other carotenoids (Hussein et al., 2006). Astaxanthin may act as a strong antioxidant by donating the electrons and reacting with free radicals to convert them into more stable products and terminate free radical chain reaction in a wide variety of living organisms. The nonpolar middle segment of the astaxanthin

molecule is a series of carbon-carbon double bonds, which alternate with carbon-carbon single bonds, termed “conjugated”. This polar-nonpolar-polar layout also allows the astaxanthin molecule to take a transmembrane orientation, making a precise fit into the polar-nonpolar-polar span of the cell membrane (Kidd, 2011). As mentioned by many authors, the antioxidant activity of astaxanthin appears to be greater than that of beta-carotene and alpha-tocopherol (Fukuzawa et al., 1998 and Naguib, 2000). However, studies from our group which evaluated the antioxidant effect of astaxanthin on leukocytes in human and animal models, showed a modest antioxidant action (Bolin et al., 2010, Guerra and Otton, 2011, Macedo et al., 2010, 17-DMAG (Alvespimycin) HCl Mattei et al., 2011, Otton et al., 2010 and Otton et al., 2011), mainly observed in the reduction of superoxide and hydrogen peroxide

production. Vitamin C is an essential micronutrient, which has been implicated in a variety of biological processes, including immune response (Maeng et al., 2009). Vitamin C or l-ascorbic acid is the body’s most important intracellular and extracellular aqueous-phase antioxidant. This antioxidant easily scavengers peroxyl radicals, superoxide anion, singlet oxygen and hypochlorite (Sies and Stahl, 1995). The oxidation of vitamin C by reacting with ROS generates the ascorbyl radical that has little reactivity, crucial to the antioxidant effect of vitamin C. Ascorbic acid is considered a physiological substrate for myeloperoxidase (MPO) and its effect on myeloperoxidase-dependent processes is widely attributed to scavenger or quencher actions on hypochlorous acid (Myzak and Carr, 2002 and Savenkova et al., 1994).

The corresponding commutation superoperators Hˆˆn(C) can be written as differences between left-side and right-side product superoperators Hˆˆn(L) and Hˆˆn(R), defined by their action on a density operator ρˆ: equation(3) Hˆˆ(C)=∑nHˆˆn(C)=∑nHˆˆn(L)-Hˆˆn(R)Hˆˆn(C)ρˆ=[Hˆn,ρˆ]=Hˆnρˆ-ρˆHˆnHˆˆn(L)ρˆ=HˆnρˆHˆˆn(R)ρˆ=ρˆHˆn Their faithful

representations have exponential dimensions, but representations in low correlation order basis sets are cheap [13]. In a given operator basis Oˆk: equation(4) Hˆˆn(L)jk=OˆjHˆˆn(L)Oˆk=TrOˆj†HˆnOˆk=Tr⊗m=1Nσˆj,m†⊗m=1Nσˆn,m⊗m=1Nσˆk,m Because dot products commute with direct products and the trace of a direct product is a product of traces, we have: equation(5) Hˆˆn(L)jk=Tr⊗m=1Nσˆj,m†σˆn,mσˆk,m=∏m=1NTrσˆj,m†σˆn,mσˆk,min which the dimension PD-1/PD-L1 cancer of individual matrices σˆn,k is tiny and does not depend on the GSK126 datasheet size of the spin system;

the computational complexity of computing Tr[σˆj,m†σˆn,mσˆk,m] is therefore O(1) and the complexity of computing one matrix element is O(N) multiplications, where N is the total number of spins in the system. With O(N2) interactions in the spin system, this puts the worst-case complexity of building the representation of the Hamiltonian in Eq. (3) to O(N3D2), where D is the dimension of the reduced basis set. The sparsity of spin Hamiltonians [19] and the fact that spin interaction networks in proteins are also sparse Molecular motor puts the practically observed scaling closer to O(N2D) – a significant improvement on the O(4N) best-case scaling of the adjoint direct product representation. This improvement is further amplified by the presence of unpopulated states even in the low correlation order subspace [8], by the existence of multiple independently evolving

subspaces [13], and by the fact that not all of the populated states belong to the propagator group orbit of the detection state [11]. Matrix dimension, storage and CPU time statistics for a 512 × 512 point 1H–1H NOESY simulation of ubiquitin (573 protons, ∼50,000 terms in the dipolar Hamiltonian) are given in Table 2. As demonstrated in Fig. 1 and Fig. 2, the simulation is in good agreement with the experimental data. The state space restriction approximation reduces the Hamiltonian superoperator dimension from 4573 ≈ 10345 to 848,530. The reduced Hamiltonian is still sparse, and therefore within reach of modern matrix manipulation techniques – the simulation shown in Fig. 1 took less than 24 h on a large shared-memory computer.

And so began one of the more remarkable pieces of biochemistry ever. On my arrival at Harvey’s lab, I was sent back to Cambridge to work with Brij Gupta and Ted Hall (the famous nuclear spy (Jackson, 1999)), to use the cutting-edge technology of electron-probe X-ray microanalysis. This technique provided the first direct proof that – as expected – the site for potassium transport was the apical membrane of the goblet cells (GCAM) unique to the caterpillar gut (Dow et al., 1984). Isolation of the goblet cell membrane should thus in turn isolate the pump protein. Back at Temple, Harvey conducted daily strategy sessions PF-01367338 clinical trial with his colleagues, the biochemist Michael Wolfersberger

and the cell biologist Moira Cioffi, while they purified the goblet cell apical membranes to an extraordinary degree, using micro-dissection and progressive ultra-sonication followed by differential and gradient centrifugation with visualization of portasomes selleck chemicals llc as the sole assay. However, even with large quantities of starting material, each two-day run produced barely enough GCAMs to quantify the protein, run the portasome assay and do a few ATPase determinations (Cioffi and Wolfersberger, 1983). The problem was solved when Bill was joined at Temple by Helmut Wieczorek who was trying to purify the same protein from the labellar sensillae of flies and had developed a micro-assay for ATPase activity

that was sensitive enough to localize the K+-stimulated ATPase to GCAM vesicles. Wieczorek’s group solubilized the vesicles and when the gels were run, they recognized that the ladder of proteins on the gel corresponded to some of the subunits of the recently discovered vacuolar proton pump, the H+ V-ATPase. However, the V-ATPase transports only H+ whereas the GCAM ATPase transports K+. Wieczorek and colleagues proposed that the V-ATPase generated a protonmotive force that drove H+ back into the cells and K+ out by a K+/2H+ antiporter (Schweikl et al., 1989). This key insight transformed the field over the next Montelukast Sodium few years, as its generality was realized; however, the discovery

would have been impossible without the superb membrane purification of Harvey, Cioffi and Wolfersberger (Wieczorek et al., 1990). Bill’s interest in H+ V-ATPases continues to this day; with a seminal symposium that he organised in Telluride and fruitful collaborations with Wieczorek and Nathan Nelson, the generality of the V-ATPase as a plasma membrane-energising force across phyla, became clear (Harvey and Wieczorek, 1997). However, attempts to clone and purify the antiporter were unsuccessful. On the colder winter days at Temple, Bill had frequently told me that he dreamed of retiring to Florida; and that is exactly what he did in 1997. However, he took with him two NIH grants, and established himself at the Whitney Laboratory of the University of Florida, where he has been actively researching ever since.

In this study, various gene copy numbers of AVR-Pita1 were identified in most of the transformants. However, the level of avirulence of these transformants remained unchanged selleck products when compared with other transformants. In fact, all of the transformants became avirulent, suggesting that the position and arrangement of AVR-Pita1 had no effect on the level

of avirulence. Previously, Khang et al. [11] identified three members in the AVR-Pita gene family and confirmed the function of each member as well as their promoters by transferring different combinations of the coding regions and promoter regions. In their study, both AVR-Pita1 and AVR-Pita2 conferred avirulence on isolates virulent toward Pi-ta-containing rice cultivars but AVR-Pita3 failed to do so [11]. These findings are consistent with the predicted role of AVR-Pita1 as an elicitor interacting specifically with the Pi-ta protein in triggering resistance in plant cells [12] and [13]. Major R gene-mediated resistance can be robust and complete, but may not be long-lasting.

That Pi-ta has been defeated by race IE1k suggests an urgent need for exploring novel approaches. In this study, we altered isolates by converting isolates back to their presumed wild-type state. When this was done, the isolates were no longer able to infect Pi-ta-carrying cultivars. For the first time, we experimentally demonstrated that Pi-ta in the U.S. cultivars recognizes the original click here AVR-Pita identified from a Chinese isolate O-137 and initially named AVR2-YAMO. Our findings also suggest that the development of a novel race carrying the AVR-Pita1 allele from isolate O-137 of the pathogen could allow the development of rice lines that have more effective, or durable, resistance

to the rice blast pathogen. We thank the University of Arkansas Rice Research and Promotion Board for financial support to Y. Dai; Barbara Valent of Kansas State University for plasmids PCB980 and PCB1003; Michael Lin, Ellen McWhirter and Tracy Bianco of USDA ARS DB NRRC; and Jin-Rong Xu of Purdue University for for the technical assistance. USDA is an equal-opportunity provider and employer. “
“Comprising approximately 50% of wheat gluten proteins, gliadins have essentially a plasticizing effect on gluten structure and mainly impart viscosity to dough [1]. Though it is generally concluded that gliadins exert mainly negative effects on overall dough strength, positive contributions of these proteins to loaf volume have also been detected [2], [3], [4] and [5]. Based on their mobility in the A-PAGE gels, as well as their different primary structures, gliadins can be divided into three groups: α-, γ- and ω-gliadins [6].

All results from this CRM fell within the acceptable range (8.82–13.2 μg/L). The results of the prepared QC saliva samples were used to calculate percentage recoveries for the 10 μg/L spiked sample, corrected for the lead level present in the blank, for both the

“Fresh” Smad inhibitor and “Device” QCs. For the “Fresh” QCs, recovery of 107.7% was observed. For the “device” QCs, recovery was 65.9%. Descriptive statistics of the sample cohort are provided in Table 1. The cohort comprised 105 paired blood and saliva samples. All participants were male (this was not an intentional discrimination by the authors, but due to the presence of very few female workers in the industries studied). There were 53 samples provided by smokers and 52 by non-smokers. The age range of participants was 18–65 years, with a mean age of 37 years old and a median AG-014699 in vivo age of 35 years old. Forty of the individuals sampled were categorised as having “no sample history”. History category 1 (Δ = ± 1 μg/dL) included 27 samples; category 2 (Δ = ± 2 μg/dL) included 42 samples; and category 3 (Δ = ±3 μg/dL) included 44 samples. The remaining 21 samples had Δ > ± 3 μg/dL and were

classified as “fluctuating history”. Summary statistics of the lead levels observed in both the blood and in the saliva samples are presented in Table 2. There were no significant differences in blood lead values between the history categories 1–3 (mean: 5.59 μg/dL, 5.40 μg/dL and 5.91 μg/dL respectively; median: all 4.00 μg/dL). Variability was also very similar for the three categories (standard deviation: 4.16 μg/dL, 3.72 μg/dL and 4.32 μg/dL, respectively). However, the blood lead values for the “fluctuating history” category were much higher (mean: 17.62 μg/dL; median: 15.00 μg/dL). Variability was also much greater in this category (standard deviation: 11.31 μg/dL). For the saliva lead values, the Vildagliptin mean and 75th percentile values are substantially lower for history category 1 than for categories 2 and 3 (mean: 19.8 μg/L, 27.8 μg/L and 29.0 μg/L, respectively; 75th percentile: 23.8 μg/L, 29.1 μg/L and 30.6 μg/L, respectively). The variability is also lower in category

1 than the other two categories (standard deviation: 14.2 μg/L, 31.9 μg/L and 32.2 μg/L respectively). However the median values do not demonstrate any significant difference (15.5 μg/L, 15.7 μg/L and 15.9 μg/L, respectively). Similarly to the results in blood, the salivary lead values for the “fluctuating history” category were much higher (mean: 66.2 μg/L; median 48.8 μg/L). Variability was also much higher (standard deviation: 66.3 μg/L) than for categories 1, 2 or 3. There were no substantial differences in the blood lead values between smokers and non-smokers. For the saliva lead values, the mean and 75th percentile values were higher (not statistically significant) in smokers than non-smokers (mean: 43.5 μg/L and 36.

The mismatch between local scale establishment of MPAs and national or international scale policies and

agreements aiming to conserve marine biodiversity, coupled with the natural tendency of administrative bodies to be insular, leads to piecemeal efforts. Integrated coastal management or ICM (Olsen and Christie, 2000), now subsumed within ecosystem-based management RG7422 ic50 or EBM (McLeod and Leslie, 2009), is a set of contextual and design principles to accommodate this need for explicit interventions with the need for seamless, regional-scale care of coastal ecosystems. But while ICM has been discussed for over 20 years, examples of its effective implementation are rare (Tallis et al., 2010 and Collie et al., 2013). Similarly, while it is increasingly recognized that management should be done at larger scales, including through the large marine ecosystem framework (Sherman, 1986) that identifies 64 large marine ecosystems (LMEs), large-scale management efforts frequently fail to generate the essential buy-in by local communities and stakeholders that is necessary for success (Christie SB431542 research buy et al., 2005 and Tallis et al., 2010). What appears to be needed is a technically simple set of procedures that can enforce a multi-scale perspective and a strongly holistic approach to management despite the diversity of agencies,

stakeholders and goals inherent in any attempt to manage coastal waters on a regional scale. We propose making

expanded use of marine spatial planning (MSP) and zoning as a framework Adenosine triphosphate that will apportion coastal waters for differing activities, while forcing a multi-target and multi-scale approach, and achieving agreed ecological, economic and social objectives (Agardy, 2010 and Tallis et al., 2010). MSP has been practiced largely in developed countries, principally focusing on conservation of coastal ecosystems (Agardy, 2010, Tallis et al., 2010 and Collie et al., 2013). Use of MSP to facilitate sustainable food production, in concert with other activities, has received very little attention, despite the great dependence on small-scale fisheries in tropical developing countries (Hall et al., 2013), where rural communities have few alternative sources of animal protein (Bell et al., 2009, Kawarazuka and Bene, 2011 and Lam et al., 2012). In these countries, effective coastal management must acknowledge this widespread dependence of poor and politically weak communities on the use of fish for food (Lam et al., 2012 and Hall et al., 2013). Acknowledging this dependence (Bell et al., 2006, Bell et al., 2009 and Mills et al., 2011) is pivotal to reconciling the largely separate agendas for food security and biodiversity conservation (Rice and Garcia, 2011 and Foale et al., 2013).