Out-of-plane tissue deformations are key morphogenetic events during plant and animal development that generate 3D shapes, such as flowers or limbs. However, the mechanisms by which spatiotemporal patterns of gene expression modify cellular behaviours to generate such deformations remain to be established. We use the Snapdragon flower as a model system to address this problem. Combining cellular analysis with tissue-level modelling, we show that an orthogonal pattern of growth orientations plays a key role in generating out-of-plane deformations. This growth pattern is most likely oriented by a polarity field, highlighted by PIN1 protein localisation, and is modulated by dorsoventral gene activity. The orthogonal growth pattern interacts with other patterns of differential growth to create tissue conflicts that shape the flower. Similar shape changes can be generated by contraction as well as growth, suggesting tissue conflict resolution provides a flexible morphogenetic mechanism for generating shape diversity in plants and animals.DOI:http://dx.doi.org/10.7554/eLife.20156.001 Plant and animal organs come in many different shapes, from pitcher-shaped leaves and butterfly wings, to orchid flowers and the convoluted shape of the brain. Unlike pottery or sculpture, no external hand guides the formation of these biological structures; they arise on their own, through sheets of cells developing into particular three-dimensional shapes. But how does this process of self-making operate? We know that patterns of gene activity are important, because mutations that disrupt these patterns change the shape of the organ. But it is not clear how these patterns lead to sheets of cells curving and bending themselves into their characteristic three-dimensional shapes.Plants are particularly useful tools for studying how three-dimensional organs form because, unlike animals, their cells do not slide relative to each other, which makes the analysis simpler. Rebocho et al. used a combination of computational modelling and cell analysis to study how the intricately shaped flowers of plants known as Snapdragons form. The experiments show that genes control the shape of Snapdragon flowers by causing groups of cells to grow at different rates and in different directions. This pattern of growth creates internal conflicts that are resolved by sheets of cells curving in particular ways, accounting for the three-dimensional shape.Rebocho et al. propose that the principles of tissue conflict resolution described in this work may also underlie the development and evolution of many other plant and animal organ shapes. A future challenge is to identify the cellular mechanisms that link patterns of gene activity to the generation and resolution of conflicting cell behaviours.DOI:http://dx.doi.org/10.7554/eLife.20156.002 Out-of-plane deformation of tissue sheets plays a fundamental part in morphogenesis. In animals, it underlies processes such as gastrulation, neurulation, convolution of the cerebral cortex, gut folding, development of imaginal discs and dorsal appendages. Several models have been proposed to account for such deformations, involving a variety of processes such as differential surface contractions, oriented tissue tensions and differential growth . In plantissue conflict resolution .A key feature of out-of-plane deformations is that they involve generation of curvature . Two mechanisms might account for the generation of local rotations for a tissue sheet. The first is that local rotations arise through forces external to the sheet pulling or pushing on particular regions. For example, petals (whorl 2) grow in between sepals (whorl 1) and stamens (whorl 3), and these adjacent organs could apply forces to shape the petal. However, homeotic mutants that change the identity of stamens to petals do not have a major effect on the complexity of whorl 2 petal shape , making To clarify the notion of tissue conflict resolution we distinguish between two types of growth: specified and resultant . SpecifiTo illustrate how patterns of specified growth may lead to out-of-plane deformations, consider a square sheet of tissue marked with circular spots  corolla has five petals united for part of their length to form a tube with five separate lobes, which diverge at their sinuses (CYCLOIDEA (CYC), DICHOTOMA (DICH) and RADIALIS (RAD) encode dorsal-specific transcription factors that repress the ventral identity gene DIVARICATA (DIV)  , 1996.10DIV is required for the development of the wedge-shaped fold. In div mutants, the wedge-shape of the lower corolla is lost and two small domes form at the foci   . The firtiation) . Prior ttiation) . During tiation) . These ctiation) . The othtiation) . Over thtiation)  and 2C–Ddiv flower has an open mouth and lacks an extended palate  or perpendicular (perK) to the polarity field. Plant cells can be readily imposed on this framework because cell topology is preserved: once a vertex is created by division, its relation to other vertices is maintained through subsequent growth (plant cells do not move relative to each other). We assume that when the area of a cell exceeds a threshold, it is divided along the shortest path through its centroid , in which the tissue is treated as a connected continuous material, termed the canvas . This iscentroid . The newcentroid . Cell wacentroid .If specified growth was isotropic and uniform, the resulting pattern of walls resembled that of div and wild-type petals showed that at 10 DAI, growth was largely oriented parallel to the proximodistal axis  and inhibited specified growth perpendicular to the polarity (perK) , while RIM promoted perK (and inhibits parK)  . A dome ts Kpar) . Virtualts Kpar)  and perpts Kpar) .Video 11In all the above cases, the axial information provided by the polarity field was critical for the resulting shape. Boosting isotropic growth in an orthogonal pattern  generated a series of bulges rather than a dome .Video 12Orthogonal directional conflict resolution thus provides a mechanism for generating out-of-plane deformations, and can be specified in several ways through a combination of orthogonal regional identities and polarity fields . Further dome shapes can be generated by combining the orthogonal directional conflict with areal and surface conflicts , or by cIn the above examples, we modelled deformations as arising through differential growth. In animals, contractions as well as growth may be involved in generating out-of-plane deformations. In early animal embryogenesis it is common for deformations to occur without overall change in size. To determine how principles of tissue conflict resolution could apply in these contexts, we modelled deformations that preserve overall size. For these purposes, contraction could be considered as equivalent to negative growth.parK) was counterbalanced by negative specified growth perpendicular to the polarity (negative perK), and gave a similar result to overall positive growth  for the lower surface, and gave a folded shape similar to that based on differential growth compare . For are compare . Such a  compare . Surfacediv and wild type. This hypothesis requires a polarity field for orienting the growth in each region. To test whether a polarity field is present and determine its pattern of orientations, we analysed PIN1 auxin transport protein distribution as this is a possible readout of cell polarity . RNA in situ hybridisation revealed that the three PIN1 genes showed detectable expression in developing wild-type petals, with all PIN1 orthologues strongly expressed in the vascular tissue and epidermis in the palate region of the lower petals . Prior to the repatterning of corolla growth in distally . This padistally , overlapdistally . PIN1 isis stage . Thus, Pdiv. Rather than modelling the entire div corolla, we first modelled the region forming the out-of-plane deformation.In light of the data above on fate mapping, cell files and PIN1 localisation, we modelled corolla morphogenesis, beginning with the simpler deformation observed in div and wild-type out-of-plane deformations develop from a curved strip of tissue at the tube-lobe boundary, encompassing the presumptive palate and lip (parK) and perpendicular (perK) to the polarity field . As PIN1 cellular localisation was only observed around the sinus and was mainly proximodistal, we made the simplest assumption that polarity is maintained as proximodistal throughout the canvas  surface in the rim to promote out-of-plane bending  led to the out-of-plane deformations protruding abaxially instead of adaxially . This wadiv model above into this ground state produced a corolla with an open mouth, a reduced palate, two domes tipped by the foci and a flat extended lip, similar to the div phenotype . These s region . To simuWith these assumptions, a wedge shape was generated that resembled that observed in wild type . The patdiv, we evaluated the contribution of each type of conflict to the final shape. Removing surface conflict led to the out-of-plane deformation protruding abaxially instead of adaxially  from the model generated phenotypes resembling those of the respective mutants  wild type (JI7 and JI2) and div-13  placed onto a glass slide. At early stages the whole petal could be flattened onto the glue. At later stages, when wedge formation was deforming the lower petals, we tried to keep the 3D shape of the petals by only flattening the distal lobe and palate-tube regions.div-13 and wild-type, we used dissected and flattened material from staging experiments, as well as the OPT bud series, to mark different morphological landmarks that delimit the wedge, and made measurements on how this region grew. The measurements were done in imageJ. We used the same landmarks for div-13 and wild-type (exceptions indicated below). We used the lateral petal midvein as the mediolateral limit of the wedge, which was visible at early stages just after petal emergence at 8 DAI. To mark the upper and lower limits of the wedge along the proximodistal axis, we used the lip-distal lobe boundary and the palate-distal tube boundary, respectively. The petal-distal lobe boundary ran along the sinus of the petals, so to mark this boundary we drew lines from the D-L petal sinus to the V-L sinus as well as the two V-L sinuses. This morphological landmark was easily marked from the time of petal emergence. The proximal wedge limit could only be marked after 14 DAI, when palate trichomes emerged. This limit could not be marked in div-13 as the lower petals did not develop palate trichomes . The rim position was visible from 14 DAI, as a furrow in flattened petals.To follow the development of the wedge region from emergence until maturity in http://cmpdartsvr3.cmp.uea.ac.uk/wiki/BanghamLab/index.php/Main_Page).Snapdragon flower buds were dissected from inflorescences, sepals removed and the buds prepared for OPT as previously described . ScanninSnapdragon inflorescences were harvested and hand cut to 1 cm thick, before fixing in phosphate-buffered saline (PBS) pH 7.5 containing 4% paraformaldehyde , 0.1% Triton-X100 and 0.1% Tween-20, overnight at 4°C. After dehydration (50% and 70% ethanol), samples were embedded in paraffin  using a Tissue-TEK VIP processor (Sakura). 8 µm sections were cut, mounted on polysine slides (VWR) and dried overnight at 42°C. Slides were dewaxed in histoclear (2x for 10 min)  and hydrated through a decreasing ethanol series  NaCl). Slides were washed in PBS solution before digesting the tissue with Pronase  for 12 min. A 0.2% (v/v) Glycine-PBS solution was used to block the Pronase activity , followed by a PBS wash and another fixation step with 4% paraformaldehyde in PBS for 10 min. After a 2 × 10 min PBS washes, the tissue charges were neutralised using a 0.5% (v/v) acetic anhydride solution made in 0.1M triethanolamine pH 8.0, to minimise unspecific binding and background. Slides were washed in PBS and dehydrated though an increasing ethanol series  and left to dry for at least 15 min. To generate specific digoxigenin-labelled riboprobes probes, the ORF of AmPIN1a , AmPIN1b  and AmPIN1c  were amplified using TAQ DNA polymerase PCR  and cloned into pCR4-TOPO TA vector  following manufacturer’s instructions. The cloned fragments were amplified using forward specific primers  and the M13F primer (pCR4-TOPO kit), column purified  followed by a phenol/chloroform extraction. Antisense probes were obtained by RNA transcription using the T7 promoter  and DIG-UTP , according to manufacture instructions. The AmPIN1a, AmPIN1b and AmPIN1c probes were hydrolysed at 60°C using 200 mM carbonate buffer pH 10.2 solution, for 80, 8 and 60 min, respectively. The hydrolysed probes were boiled in 50% formamide  solution for 2 min and left on ice to cool, before adding the hybridisation buffer , 2500 µl Deionized formamide , 62.5 µl tRNA , 125 µl Denhardt’s, 437.5 µl RNase-free water, 1250 µl 50% Dextran Sulphate ). Two microliters of hydrolysed probe plus 100 µl of hybridisation buffer were used per slide, and covered with Hybrislip hybridisation cover . Slides were hybridised in a humid box overnight at 50°C. Next day, slides were washed 3 times in 0.2x SSC solution at 55°C for 25 min. Single stranded RNA was digested with RNaseA  in NTE buffer  at 37°C for 30 min. Slides were washed in 100 mM Tris.NaCl pH7.5 solution and then blocked using a freshly made 0.5% (w/v) blocking reagent  in the same buffer, for 1 hr at room-temperature (RT). After a 30 min wash in 1% (w/v) BSA  (made in 100 mM Tris.NaCl pH7.5 with 0.3% Tritonx100), slides were hybridised with a 1:3000 dilution of Anti-digoxigenin-AP antibody  for 90 min. Slides were washed in 100 mM Tris.NaCl pH7.5 with 0.3% (v/v) tritonx100, 4 times for 25 min. Triton-x100 was removed from slides by washing them in 100 mM Tris.NaCl pH7.5 for 5 min. Before detection, the slides were washed in a 100 mM Tris.NaCl pH9.5 to equilibrate the pH. Detection was performed overnight using a NBT/BCIP (Promega) in 100 mM Tris.NaCl pH9.5 plus 50 mM MgCL2. The in situ experiments were performed three times.div mutant lower petals at various stages of development = 6. Number of replicas for calcofluor staining and whole mount PIN1 immuno of wild-type mutant lower petals at various stages of development = 11. Replicas gave similar results for similar developmental stages.Protocol adapted from Conti and Bradley . For secThe AmPIN1a, AmPIN1b, AmPIN1c and AmPIN1  antibodies were produced in rabbit by Cambridge Research Discovery (CRB) using the following predicted antigenic peptide sequences present in the cytosolic loop domain. Peptide sequence for AmPIN1a -SRGPTPRPSNFEEE, AmPIN1b – HRGNNEDGYLERDEL, AmPIN1c – FSPASTKKKGENGKD and AmPIN1 -IYSMQSSRNPTPRGS. The clearest signal was obtained with the AmPIN1a antibody. The AmPIN1 antibody gave similar results but with more background.http://imagej.nih.gov/ij/). Fluorescent immunolocalisation results were imaged using a Leica SP5 II confocal microscope and x25 water dipping lens. Images were acquired in a format of 1024 × 1024, with a line average of 4, scan speed of 600 Hz and pinhole of 1 airy unit. Excitation for Alexa 594 on laser 20% was with a 561 laser line, with a detection band of 570–630 nm. Calcofluor was imaged with a 405 diode laser and detection at 450–500 nm. Z stack images were at 1 µm/section. Image reconstruction was performed using the ImageJ software.Scanning electron microscopy was carried out as described in Vincent and Coen . In situPIN1 polarity was quantified using the PinPoint software, developed in MATLAB to analyse gene expression in cell boundaries. A composite stack of Anti-PIN1-Alexa594 and calcofluor staining was loaded into the program. For each cell segmentation, we determined which cell the PIN signal belonged to by manually scrolling through the z-stack. In ambiguous cases this determination was aided by PIN signal following the curvature of cell walls . A repretissue conflict resolution.Mathematically, growth of a region is described by a growth tensor which can have both a strain (symmetric) and rotational (skew-symmetric) component . A speciIn some cases, the potential conflicts in growth may be fully resolved through rotations, in which case the only difference between specified and resultant growth tensors is in the rotational component and there is no residual strain. For example, a conformal map is a planar deformation in which local rotations are generated through a gradient in isotropic specified growth without producing residual strain . If the See Supplementary Material and methods for a full description of tissue-level modelling. All models used can be downloaded from:http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_Elife_Rebocho_2016/GPT_TissueConflicts.zipparK) and perpendicular (perK) to the local polarity, established by taking the gradient of a diffusible factor POLARISER (POL). The production and degradation of POL depends on a polarity regulatory network (PRN). To visualise specified anisotropy, we calculate Kaniso = ln (parK /perK) and display its local value using a colour scale. If growth is isotropic (parK = perK), Kaniso = 0. Specified areal growth rate is given by areaK = parK + perK.Models are based on the Growing Polarised Tissue framework (GPT-framework) . Tissue,To explore growth patterns that could give rise to the observed cell wall staining with calcofluor, cell division is modelled using the GPT framework. Cells are drawn on the canvas and their vertices displaced with the canvas as it grows. New walls and vertices introduced when the cell area reached a threshold value. Division walls take the shortest path through the cell centroid. The model has three stages: (T0), when the canvas is established and the initial cells are introduced; (T1), a first phase of growth, and (T2) a second phase of growth. To distinguish between the age of cells walls formed at each stage, we specify that walls at an initial time point (T0) are marked with thick blue lines, cell walls that arise during T1 are shown with thinner green lines and cell walls that arise during T2 are marked with very thinner white lines. A proximodistal polarity field is established at T0 using the GUI. We explore three growth patterns:1. Uniform isotropic growth,2. High 3. High To illustrate how various types of tissue conflict resolution lead to curvature, we use an initial square with very slight curvature and marked with circular clones.To model uniform specified isotropic growth the KRN equations are:where Knor is specified growth rate in canvas thickness.To model uniform specified anisotropic growth, a polarity field is established by producing POL at the bottom of the canvas (through factor BOTTOM) and fixing it to a low concentration at the top (through factor SINK). The gradient of POL defines the local polarity. For uniform anisotropic specified growth, the KRN equations are:To model surface conflict with growth, the KRN equations are:To model areal conflict with growth, the KRN equations are:where To model directional conflict, a convergent polarity is established by producing POL at the centre of the canvas (by factor FOCI) and degrading at the periphery (by factor EDGE). The KRN equations are:As in As in To model orthogonal directional conflict in the context of a convergent polarity field, the same polarity field as above was used, with KRN equations:where the distribution of To model a T-shaped directional conflict in the context of a convergent polarity field, the KRN equations are:where e canvas .To model a L-shaped directional conflict in the context of a convergent polarity field, the KRN equations are:where To model a directional conflict for a vertical domain in the context of a convergent polarity field, the KRN equations are:To model a directional conflict for a vertical domain in the context of a convergent polarity field, the KRN equations are:To model a directional conflict in the context of a parallel polarity field, the polarity field was established as for To model areal conflict for an orthogonal domain, the KRN equations are:To model directional conflict in the context of an orthogonal polarity field, POL is initially produced at the bottom of the canvas (SOURCE) and degraded at the midpoint along the top of the canvas (SINK). Polarity along the vertical midline region is locked to create a polarity channel. while also acting as a weak sink for the SIDE regions where POL is now produced. The KRN equations are:where To model a combination of directional conflict with enhanced areal growth rates  in the orthogonal domains we used the polarity field as in To model a combination of surface conflict and orthogonal directional conflict in the context of a convergent polarity field  and 12–24 DAI (phase II). POL production is promoted by SOURCE, expressed at the most proximal region of the rectangle, and degraded at SINK, expressed at the most distal region of the canvas, generating a proximodistal polarity field. By 10 DAI, the polariser gradient, the expression pattern of the identity factors and diffusible factors (prefixed with ‘s’) are established, and then fixed to the canvas for the rest of the simulation. Regional factors are established along three axes:Dorsoventral axis: the dorsally expressed gene RAD is expressed at the most lateral petal edges and produces a signal (sRAD) that diffuses into the lateral petals (hinge region) and inhibits the ventrally expressed gene DIV.Proximodistal axis: PALATE (PLT) is expressed in the proximal region. PALATEPROX (PLX) is expressed in the most proximal part of the palate. RIM is expressed at the distal limit of PLT. RIM promotes production of sRIM which diffuses and activates BRIM when the levels of sRIM are higher than 0.01. LIP is distal to RIM and is subdivided in the proximal region, LIPCLIFF (LIF), and a distal region, LIPDISTAL (LIS).Mediolateral axis: graded factors are sMED, which is centred on the petal midvein, sSEC, which is centred on the secondary veins, and sLAT which is centred on the junction between petals.Sectors (circular regions) were induced at around 12.5 DAI, with initial sector size scaled to the initial size of a cell (~10 µm). Growth in canvas thickness was maintained at 0.44 %/h in all models. are inhibited at the hinge by the action of sRAD, to keep the hinge region short and narrow. parK is promoted at the distal lip (LIS) region to generate the asymmetric lip. The KRN phase I equations are:Growth is higher in z) promotes factor yz by an amount x, and inh  inhibits factor yz by an amount x  and midvein regions (sMED). The full KRN is:The KRN is similar to that for At the start of phase II polarity is deflected by establishing a new site of POL degradation at the SINUS . The deflection of polarity was made specific to the adaxial (B) surface of the canvas by freezing polarity on the A surface, preventing it from reorienting. by LIS and the inhibition of  and  by sRAD are the same as in div model for phase II. Relative to phase I, the promotion of  by LIF and DIV is reduced. The orthogonal directional conflict is similar to that in div phase II, except that  promotion by sRIM is boosted by DIV and extended to the LIP regions. The extended region was kept narrow by SEC. Inhibition of  by sLAT is reduced in the LIF region to allow for more  and the formation of the protruding lip in the ventral petal. The inhibition of  by sMED is reduced by PLT in combination with DIV to prevent the palate from becoming too narrow. The full KRN for phase II is:The boost of A summary of the KRN is given in  at sRIM and  at ventral lip removed  Step-up phase (9 DAI), when the polariser gradient, the expression pattern of most identity and signalling factors are established (patterns are maintained throughout simulation unless otherwise stated) (2) 10–13 DAI, during which EARLY factor is expressed and (3) 14–24 DAI, during which LATE factor is expressed. The PRN is as described in the set-up phase for the previously published model , and theAll genetic interactions in the published model for wild type under the control of DIV or LTS (LATERAL PETALS) which modulate specified growth rates in lower petals (see red equations below) are removed to produce a corolla without out-of-plane deformations in the lower petals.KRN equations for the ground state are:Summary of KRN for ground state is given in Figure 12I.Several new regions are created to incorporate genetic interactions defined in the wedge models described in Same as the ground stage with the following modifications boosted by LIPDISTAL (LIS) in lower petals while inhibited by HINGE. This activation is reduced by LATE (K.1.16 and K1.17). and  beween A  and B  surfaces at the sRIM introduced, to promote petal bending  and furrow formation The differential growth in  in DISTAL LOBE (DTL) promoted at the hinge region (K.1.19). inhibited by MED in combination with LIF and UPTUBE, particularly at the rim of the lower petals (K.1.21). at the petal junctions  specifically at the regions of LIPCLIFF (LIF) and distal palate (UPTUBE), with the exception of the lateral-dorsal LIP region where Kpar is inhibited (K.1.22). Additionally,  at the rim is inhibited (K.1.23).The proximodistal arms of the orthogonal directional conflict are specified by boosting  with sRIM flanking the petal junctions, excluding the dorsal petal junction, and inhibiting  in with LAT and MED in combination with LIP and PLT (K.2.11-K.2.13).The mediolateral arms of the orthogonal directional conflict are established by promoting  in distal petal regions promoted by removing K.2.5 and modifying K.2.4c)The KRN equations are:div mutant, showing only new interactions (green), and modified interactions (blue), is given in A summary of KRN for the Equations as in previous section with those establishing the orthogonal growth orientations  removed.div corolla model. DIV modulated the growth rates and orientations across the corolla as follows:The DIV factor is introduced into the above  with LIS (modified K.1.16a and K.1.17a)DIV decreases  with LIF (K.1.24 and K.1.25).DIV promotes  with PLT (K.1.26 and K.1.27).DIV promotes  with MED in the ventral petal to generate ventral furrow (K.1.28).DIV inhibits  into the LIP at the position of the secondary veins (sSEC) (K.2.14).DIV extends the region of high  when above a certain threshold  (K.2.15).DIV inhibits  in the lateral petal lobe, keeping the distal edge of the LIP narrow and allowing the proximal region of the lip to bulge out slightly (K.2.16). This is further enhanced by the differential surface  at the LIP (K.5.3 and K.6.3).DIV inhibits  in the A surface. This allows the lower lips to bend upwards (K.3.6). This is further enhanced by the differential surface  in the same region (K.5.2a and K.6.2a)DIV promotes surface conflict the lip-lobe boundary (LPB) by inhibiting  with RIM (K.4.3a).DIV promotes DIV also activated a new region of polariser degradation at the SINUS  at the repatterning stage (14 DAI). Upon the activation of this new polarity sink, the polarity field deflects towards the sinus. The deflection of polarity is kept specific to the adaxial (B) surface of the canvas by freezing the polarity at the A surface, preventing it from reorienting.KRN equations are:Summary of KRN for wild-type depicting the DIV-dependent interactions alone (green and bold interactions) is given in -type Snapdragon corolla, we removed each of the conflicts independently.To test the contribution of the different types of tissue conflicts to the shape of the wildOrthogonal conflict equations  removed.Region of polariser degradation at the SINUS removed.Surface differential equations K.3-K.6 removed.Areal growth rates normalised as in  In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by Naama Barkai as the Senior Editor and Reviewing Editor. The following individual involved in review of your submission has agreed to reveal her identity: Ottoline Leyser (Reviewer #2).Thank you for submitting your article "Generation of shape complexity through tissue conflicts" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.The authors study the process of tissue deformation, focusing on the petal deformation during the development of the bee landing pad in the snapdragon flower. The key question addressed is how such deformation results from individual cell behavior. As main tools, the authors combine experimental methods that allow to quantitatively follow tissue growth with computer simulations. As a main result, the authors propose the framework of 'tissue conflict', the idea that deformation can result from differences in the growth behavior of individual cells, and which result from specific patterns of gene expression at the cellular and tissue level.All reviewers recommended this paper as an excellent contribution to this field that should be of wide general interest because of the important conceptual advance in provides.As you will see below, however, there are points raised which require clarification before publication. Most of these points do not require new data but a better explanation and/or exploration of the existing data and its interpretation, and wider consideration of alternative interpretations. We would like to ask you therefore to address all requests.Reviewer #1:The experiments and modeling aimed at elucidating the role of DIV in shaping snapdragon flowers provide a nice complement to other recent works from the Coen lab  illustrating how genetically specified growth and mechanics can shape organ form. In this framework the concepts of specified and resultant growth have been very valuable.A systematic examination of growth patterns leading to out-of-plane deformations is interesting and useful for the understanding of the emergence of organ form. The simulation study at the start of the manuscript is a step in this direction, and extending this exploration into something more substantial would represent a significant contribution.A key difficulty with the manuscript is that the central concept of "tissue conflicts" is not sufficiently well-defined. Specifically, it is not clear how "tissue conflicts" are related to aspects of growth (specified or resultant) or mechanics . Comments in the manuscript seem to imply that "conflicts" either correspond to situations when specified growth induces residual stresses , or growth is non-uniform. Either case seems somewhat problematic.Residual stresses may in some cases be sufficient to generate out of plane deformations, however it is unclear whether they are from a theoretical perspective necessary. Consequently, it is unclear whether and to what degree residual stresses drive generation of 3D forms, or are a common by-product of growth that sometimes feeds back to geometry.Similarly, non-uniform growth does not necessarily lead to out of plane deformations. For instance, Coleocetae has very non-uniform growth but none the less remains flat .In either case, it is unclear what conceptual clarity is gained by introducing the notion "conflicts" or if there can be a proper mathematical conceptualization of a conflict-something which we have for residual stresses and growth. The danger therefore is that precise formulations are replaced with an appealing but imprecise notion.Specific substantive comments:1) Initial cell geometry presumably has a strong impact on the cell division patterns in the cell file simulations presented in 2) Cell divisions in cell file simulations are performed by splitting cells along the shortest wall passing through the centroid. As this divides cells according to Errera's rule, it is unclear why the authors have chosen to cite Besson and Dumais (PNAS 2011) instead of Errera's original manuscript (Errera L (1886) Sur une condition fondamentale d'équilibre des cellules vivantes.). The simulated patterns presented in 3) Examining the longitudinal midsections of WT flowers in 4) The PIN quantification tool is interesting. A major challenge however is how to confidently quantify amount of signal at each side of the wall. The two flanking membranes are very thin and the signal is generally not sufficiently discrete in the magnifications they are looking. I can see how quantification would work for total amount of signal in the two sides flanking a wall but if they can quantify each side they need to explain the method more clearly. How do they deal with problems introduced by many sections being oblique which would skew the relative signal to the wall or slight non-uniformity in staining? How does calcofluor affect the method? Overall it would seem appropriate to provide information on fidelity and accuracy of the method.Reviewer #2:This paper introduces the idea of tissue conflict as a "general framework for viewing out-of-plane deformations with or without overall growth" during morphogenesis. I prefer the term "framework" as used here, to "mechanism" as used elsewhere in the paper. The value of this framework is illustrated in the context of the analysis of petal deformation during the development of the bee landing pad in the snapdragon flower. The tissue conflict concept extends a conceptual toolbox generated by this team, encapsulated in a computational modelling environment. This work has provided important insights into the process of morphogenesis, which remains a largely enigmatic area of developmental biology because of the difficulty of thinking coherently in 4D. The addition of the tissue conflicts idea seems to me very promising, and this is successfully illustrated by the insights it provides into petal deformation, as regulated by the DIV gene.The paper has the difficult task of presenting 4D results, both in general and in the specific case of the snapdragon corolla. The authors do a good job of leading the reader through these complexities. I have suggested some additions below that would have helped me further, but I recognize that different people will find different narratives/illustrations helpful.In the Discussion, the authors consider how their framework for the analysis of morphogenesis compares to others in the field. They also consider the molecular-cellular basis for the properties they propose. These aspects are extremely helpful in allowing the reader to understand the relationship between the various heuristics currently in use.Overall, I find this paper to be an excellent contribution to this field that should be of wide general interest because of the important conceptual advance in provides.My specific suggestions for improvement are:1) For me the OPT sections presented in 2) I would have liked a more precise definition of exactly how the red, yellow and orange inferred growth orientation lines were drawn. For example, in 3) I would have found it helpful if 4) It would be helpful if the Discussion included a section on how resultant growth might be generated at the cellular level.[Please note I did not review the detailed computational model]Reviewer #3:This is an elegant and overall well-executed study on morphogenesis in snapdragon petals. In addition, the paper is written enthusiastically and pedagogically. I nevertheless have a few reservations.1) "Growth conflict", as termed by the authors, is a concept that has a long history including in previous work of the Coen group. It may be called "embedding of surfaces" in mathematics (e.g. work of John Nash), "incompatible strain" in applied mathematics  or "non-Euclidian metric" in physics , as well in developmental biology . The main contribution of the present study is to characterize a case were spatial differences in growth are directional .2) It is possible to achieve the same 3D shape by various patterns of 2D growth, notably a pattern with no conflict . What is the experimental evidence that leads the authors to exclude an explanation with no conflict?3) As stated by the authors, the 3D shape arises from residual stresses due to the spatial differences in growth rate or direction. However, they neglect mechanical stresses/forces due to other floral organs. Are other organs really negligible? For instance, is petal shape influenced by homeotic conversions of stamens?4) It is unclear what are the causal links between directional growth, cell divisions, and/or PIN1a polarity, and the putative underlying polarity field. How far do cell divisions show the main direction of growth? How independent is PIN1a localisation from the orientation of recent divisions? […] Reviewer #1:[…] A key difficulty with the manuscript is that the central concept of "tissue conflicts" is not sufficiently well-defined. Specifically, it is not clear how "tissue conflicts" are related to aspects of growth (specified or resultant) or mechanics . Comments in the manuscript seem to imply that "conflicts" either correspond to situations when specified growth induces residual stresses , or growth is non-uniform. Either case seems somewhat problematic.Residual stresses may in some cases be sufficient to generate out of plane deformations, however it is unclear whether they are from a theoretical perspective necessary. Consequently, it is unclear whether and to what degree residual stresses drive generation of 3D forms, or are a common by-product of growth that sometimes feeds back to geometry.Similarly, non-uniform growth does not necessarily lead to out of plane deformations. For instance, Coleocetae has very non-uniform growth but none the less remains flat .In either case, it is unclear what conceptual clarity is gained by introducing the notion "conflicts" or if there can be a proper mathematical conceptualization of a conflict-something which we have for residual stresses and growth. The danger therefore is that precise formulations are replaced with an appealing but imprecise notion.Based on the comments of this and the other reviewers we realise that the term ‘tissue conflict’ was too readily confused with residual stress. As the key point about tissue conflict is the way it becomes resolved to generate local rotations and curvature, we have changed the name to ‘tissue conflict resolution’ and defined it more clearly in the Introduction (see response to referee #2 below), and have given a more mathematical formulation in the Materials and methods. In particular, we have clarified that tissue conflict resolution refers to a mechanism for generating tissue rotations through differential growth, as distinct from rotations arising through external forces. We also cite a recent review covering planar and well as out-of-plane tissue conflict resolution . The mathematical formulation given in the Materials and methods is below:“Definition of tissue conflict resolution. Mathematically, growth of a region is described by a growth tensor which can have both a strain (symmetric) and rotational (skew-symmetric) component (Hejnowicz and Romberger 1984). […] Some residual strain is inevitable in cases of tissue buckling , as the two surfaces of the tissue grow to a different extent, even though their specified strains are identical.”Specific substantive comments:1) Initial cell geometry presumably has a strong impact on the cell division patterns in the cell file simulations presented in div”, seventh paragraph) and included a supplementary figure  Cell divisions in cell file simulations are performed by splitting cells along the shortest wall passing through the centroid. As this divides cells according to Errera's rule, it is unclear why the authors have chosen to cite Besson and Dumais (PNAS 2011) instead of Errera's original manuscript (Errera L (1886) Sur une condition fondamentale d'équilibre des cellules vivantes.). The simulated patterns presented in We thank the reviewer for raising these points and have modified the citations and explained the method used more fully:“We assume that when the area of a cell exceeds a threshold, it is divided along the shortest path through its centroid . The new wall is then shortened slightly to give more realistic angles (Nakielski 2000).”3) Examining the longitudinal midsections of WT flowers in plena mutants, in which stamens are replaced by petals, corolla shape in whorl 2 is similar to wild-type. We now cite this finding in the Introduction .The reviewer rightly points out that the corolla tube follows the shape of the anther for some of its length and raises the question of whether the anther may have a role in shaping the petal. One argument against this is that in 4) The PIN quantification tool is interesting. A major challenge however is how to confidently quantify amount of signal at each side of the wall. The two flanking membranes are very thin and the signal is generally not sufficiently discrete in the magnifications they are looking. I can see how quantification would work for total amount of signal in the two sides flanking a wall but if they can quantify each side they need to explain the method more clearly. How do they deal with problems introduced by many sections being oblique which would skew the relative signal to the wall or slight non-uniformity in staining? How does calcofluor affect the method? Overall it would seem appropriate to provide information on fidelity and accuracy of the method.We have added some close-up images of cells in the Supplementary material  showing Reviewer #2:This paper introduces the idea of tissue conflict as a "general framework for viewing out-of-plane deformations with or without overall growth" during morphogenesis. I prefer the term "framework" as used here, to "mechanism" as used elsewhere in the paper. The value of this framework is illustrated in the context of the analysis of petal deformation during the development of the bee landing pad in the snapdragon flower. The tissue conflict concept extends a conceptual toolbox generated by this team, encapsulated in a computational modelling environment. This work has provided important insights into the process of morphogenesis, which remains a largely enigmatic area of developmental biology because of the difficulty of thinking coherently in 4D. The addition of the tissue conflicts idea seems to me very promising, and this is successfully illustrated by the insights it provides into petal deformation, as regulated by the DIV gene.We thank the reviewer for raising this valuable point about mechanism versus framework. It is understandable as we did not explicitly mention the alternative mechanism, which is that external forces drive tissue rotation. To clarify this point, we have clarified tissue conflict resolution and the alternative mechanism in the Introduction:“A key feature of out of plane deformations of a tissue sheet is that they involve generation of curvature . […] We refer to this second mechanism, in which heterogeneity of specified growth within the tissue leads to local rotations that reduce potential stresses, as tissue conflict resolution .”The paper has the difficult task of presenting 4D results, both in general and in the specific case of the snapdragon corolla. The authors do a good job of leading the reader through these complexities. I have suggested some additions below that would have helped me further, but I recognize that different people will find different narratives/illustrations helpful.In the Discussion, the authors consider how their framework for the analysis of morphogenesis compares to others in the field. They also consider the molecular-cellular basis for the properties they propose. These aspects are extremely helpful in allowing the reader to understand the relationship between the various heuristics currently in use.Overall, I find this paper to be an excellent contribution to this field that should be of wide general interest because of the important conceptual advance in provides.My specific suggestions for improvement are:1) For me the OPT sections presented in We thank the reviewer for bringing this problem to our attention, which indeed reflects the complexity of conveying shape change in 4D as the reviewer points out. Currently we give the mature flower phenotype first  and then2) I would have liked a more precise definition of exactly how the red, yellow and orange inferred growth orientation lines were drawn. For example, in We thank the reviewer for pointing out this issue. Confusion seems to have arisen in relating the zoomed-in and zoomed-out versions. This is because we chose to show only the clearest regions of oriented division in the zoomed-out version. Thus, only the left region of the box from B is shown as red lines in the zoomed-out version. We have clarified this point by giving a fuller explanation in the figure legends and by correcting the zoomed-in version of B with some extra yellow lines that had been left out by mistake.3) I would have found it helpful if We thank the reviewer for this suggestion. We have revised 4) It would be helpful if the Discussion included a section on how resultant growth might be generated at the cellular level.We thank the reviewer for raising this point. We did not include a more detailed discussion of cellular mechanisms to keep the paper short. We have now given a more detailed description of cellular level analysis in a recent review  and cite this in the paper at the end of the Discussion.[Please note I did not review the detailed computational model]Reviewer #3:This is an elegant and overall well-executed study on morphogenesis in snapdragon petals. In addition, the paper is written enthusiastically and pedagogically. I nevertheless have a few reservations.1) "Growth conflict", as termed by the authors, is a concept that has a long history including in previous work of the Coen group. It may be called "embedding of surfaces" in mathematics (e.g. work of John Nash), "incompatible strain" in applied mathematics  or "non-Euclidian metric" in physics , as well in developmental biology . The main contribution of the present study is to characterize a case were spatial differences in growth are directional .As with our response to referee #1 we have clarified our definition of tissue conflict resolution in the Introduction and Materials and methods, to make it clearer that it is a mechanism for generating local rotations, whether or not residual strain is involved. We agree with the reviewer that a major contribution of our paper is to characterise a case where deformation involves conflicting orientations of growth, but we felt it important to place this type of interaction in relation to other forms of tissue conflict resolution.2) It is possible to achieve the same 3D shape by various patterns of 2D growth, notably a pattern with no conflict . What is the experimental evidence that leads the authors to exclude an explanation with no conflict?As we now mention in the Introduction, curvature can arise without tissue conflict resolution through external forces being applied to the tissue. We point out that the normal corolla shape of organ identity mutants argues against this type of mechanism playing a major role . There can be cases of tissue conflict resolution in which no residual strain is generated . However, this does not apply to the buckling mechanisms we describe and give evidence for , as residual strains are necessarily generated as the two surfaces of the tissue attain different resultant areas (even though they are specified to be the same).3) As stated by the authors, the 3D shape arises from residual stresses due to the spatial differences in growth rate or direction. However, they neglect mechanical stresses/forces due to other floral organs. Are other organs really negligible? For instance, is petal shape influenced by homeotic conversions of stamens?plena mutants, where stamens are converted to petals, is similar to that in wild type, indicating that stresses from whorl 3 do not have a strong effect on petal shape.We thank the reviewer for raising this point. We have now pointed out in the Introduction that an alternative to tissue conflict resolution is that deformations arise through forces from other tissues. Evidence against this come from the observation that corolla shape in whorl 2 in 4) It is unclear what are the causal links between directional growth, cell divisions, and/or PIN1a polarity, and the putative underlying polarity field. How far do cell divisions show the main direction of growth? How independent is PIN1a localisation from the orientation of recent divisions?We have clarified the causal relationships between cellular behaviours and tissue growth in a recent review , now cited in our paper. For our simulations we make the plausible assumption that the plane of cell division does not directly direct growth but reflects the pattern of growth. We see a correlation between PIN1a localisation and orientations of division walls, the most notable being the correlation between diagonal walls and deflected PIN1a polarisation (noted in the sixth paragraph of the Discussion).


The therapeutic picture for HFpEF has been less favorable than HFrEF. Other than an emphasis on rigorous control of hypertension, atrial fibrillation, and fluid retention, there is relatively little new that can be offered to those patients. Regular exercise is one of the few interventions which may offer modest improvement in peak exercise capacity in such patients – as evident in the PARIS study.3 The apparent failure of pharmacotherapy stems from the fact that HFpEF can be multifactorial and the molecular pathways remain largely undefined.1Heart failure with preserved ejection fraction (HFpEF) has emerged as a major cause of cardiovascular morbidity and mortality in last decades.4 and may be considered as a therapeutic option for those who are intolerant of ACE inhibitors or ARB (class IIa recommendation).5 Despite lack of clinical evidence, nitrates are also commonly prescribed by practicing clinicians to improve exercise capacity in patients with HFpEF. Approximately 15 to 50% of patients with HFpEF are treated with nitrates,7 however it may predispose them to excessive hypotension and other adverse effects.The therapeutic benefits of nitrates in cardiovascular medicine have been known for a long time, even during the medieval period . Accordi9 It is mainly synthesized from the amino acid L-arginine by a family of NO synthase (NOS) enzymes. The synthesis of NO by vascular endothelium via endothelial NOS (eNOS) is responsible for the vasodilator tone that is essential for regulation of vascular homeostasis and blood pressure.10 In the central nervous system, NO – synthesized by neuronal NOS (nNOS) - is a neurotransmitter involved in several brain functions including the formation of memory. Moreover a network of non-cholinergic non-adrenergic nerves operate through NO dependent mechanism which mediate some of the neurogenic vasodilation and regulate various gastrointestinal, respiratory, and genitourinary functions. 9 In systemic inflammatory disorders such as sepsis and severe gastroenteritis, NO level is greatly increased owing to up regulation of inducible NOS (iNOS) activity.11Nitric oxide (NO) is a critical regulator of vascular homeostasis, neurotransmission, and home defense.2−) and nitrate (NO3−) are the oxidative end products of endogenous nitric oxide (NO) metabolism. In addition, both can be provided for in diet. Cured meat and bacon are rich in NO2−, while many vegetables are rich in NO3−. Interestingly, a plate of green leafy vegetables such as lettuce or spinach contains more NO3− than is formed in vivo by NOS.8Nitrite ,16 myoglobin (in muscles),17 neuroglobin (in brain and retina),18 molybdenum-containing enzymes ,19 and components of the mitochondrial electron transport chain21 are involved for further reduction to NO  in the heart, which is largely mediated by inhibition of mitochondrial complex I and IV.23All these pathways require low oxygen tensions to effectively generate NO. Therefore the generation of NO by this pathway is greatly enhanced during hypoxia and acidosis, ensuring NO production in situations for which the oxygen-dependent NOS enzyme activities are compromised.2− and NO3− must be distinguished from the anti-anginal organic nitrates (nitroglycerin) and nitrites (amyl-nitrite). Organic nitrates and nitrites are much more potent than NO2− in terms of vasoactivity. The in-vivo bioactivation of organic nitrates requires metabolism into NO2− and NO by mitochondrial aldehyde dehydrogenase and other enzymes.24The biological activities of the inorganic NONew England Journal of Medicine Journal in November 2015) provides insights into the overall effect of nitrates on activity tolerance in such patients.25The overall effect of nitrates in patients with HFpEF is uncertain and not extensively studied. The Nitrate’s Effect on Activity, Tolerance in Heart Failure with Preserved Ejection Fraction (NEAT-HFpEF) trial , 50 years old or more, who were randomly divided into two groups with subsequent crossover. The first group received gradually uptitrated isosorbide mononitrates from 30 mg to 60 mg to 120mg once daily for 6 weeks, while the other group received placebo for 6 weeks with subsequent crossover to each other group for 6 weeks. Each group was assessed for the daily activity level with accelerometer units during the 120mg phase as a primary end point . The secIn the group receiving the 120-mg dose of isosorbide mononitrate, as compared with the placebo group, there was a non-significant trend toward lower daily activity  and a significant decrease in hours of activity per day  . Activit26Isosorbide mononitrate did not improve the daily activity level, exercise capacity, quality of life, or NT-proBNP levels in patients with HFpEF. In contrast to its effects in patients with HFrEF, nitrates were associated with a dose-dependent decline in daily activity levels in patients with HFpEF. Patients who received nitrates had numerically lower activity time, quality of life scores and higher NT-proBNP. They also showed statistically significant reductions in systolic blood pressure, compared to placebo group. This may be related to the pathophysiologic differences between the two HF disorders. Increased ventricular and vascular stiffness, autonomic dysfunction, chronotropic incompetence, and altered baroreflex sensitivity – common in HFpEF – may limit the hemodynamic benefits of nitrates.27 Furthermore, the results may have been limited by the rapid dose escalation of nitrate therapy. This class of patients are relatively sensitive to changes in hemodynamics, thus more gradual dose escalation might have yielded different results.The current study provides a very strong signal that nitrates have no benefit and may be detrimental in patients with HFpEF. However, NEAT-HFpEF is not a very large study. It included 110 patients only, and there is still no consensus regarding the entry criteria for patients with HFpEF in all trials.28The assessment of daily activities using patient-worn accelerometers is a unique feature in the current study. It is an excellent objective measure of exercise tolerance and it provides unique quantitative information about the impact of therapies on patients’ daily functional status, rather than intermittent repetition of coached exercise tests or memory-dependent quality-of-life questionnaires.29The decline in daily activity levels (18 minutes per day) which was observed in the nitrates group is clinically meaningful. Prior observational studies have shown that even a 10-minute reduction in activity per day in patients with HFrEF was associated with adverse outcomes.Empiric use of long-acting nitrates to improve symptoms in HFpEF is not beneficial and it may have adverse effects on exercise tolerance. Inorganic nitrite or nitrate may enhance nitric oxide bioavailability preferentially during exercise and may be more effective and have fewer side effects than organic nitrates.


The cellular compartment analysis of temporal activity with fluorescence in situ hybridization for the immediate-early gene Arc was then used to identify the principal cell populations that were active during two distinct epochs of random foraging in different environments. This approach enabled the extent to which rats could discriminate two similar objects to be related to the ability of CA3 neurons to update across different environments. In both young and aged rats, there were animals that performed poorly on the LEGO object discrimination task. In the aged rats only, however, the poor performers had a higher percent of CA3 neurons that were active during random foraging in a novel environment, but this is not related to the ability of CA3 neurons to remap when the environment changed. Afferent neurons to CA3 in LEC, as identified with the retrograde tracer choleratoxin B (CTB), also showed a higher percentage of cells that were positive for Arc mRNA in aged poor performing rats. This suggests that LEC contributes to the hyperactivity seen in CA3 of aged animals with object discrimination deficits and age-related cognitive decline may be the consequence of dysfunction endemic to the larger network.Age-related memory deficits correlate with dysfunction in the CA3 subregion of the hippocampus, which includes both hyperactivity and overly rigid activity patterns. While changes in intrinsic membrane currents and interneuron alterations are involved in this process, it is not known whether alterations in afferent input to CA3 also contribute. Neurons in layer II of the lateral entorhinal cortex (LEC) project directly to CA3 through the perforant path, but no data are available regarding the effects of advanced age on LEC activity and whether these activity patterns update in response to environmental change. Furthermore, it is not known the extent to which age-related deficits in sensory discrimination relate to the inability of aged CA3 neurons to update in response to new environments. Young and aged rats were pre-characterized on a LEGO Specifically, within 2 min of behavior-related activation of a neural ensemble, Arc RNA first appears in the nuclei of principal neurons at discrete sites of genomic transcription. After about 10 min, Arc RNA begins to leave the nucleus and accumulates in the cytoplasm, where it can be detected 15–30 min after activation  and twelve young  male F344 × Brown Norway F1 rats from the NIA colony (Taconic) served as experimental subjects. Rats were housed individually in standard Plexiglas cages and maintained on a 12-h reversed light/dark cycle (lights off at 8:00 a.m.). All manipulations were performed during the dark phase of the cycle. Rats were given 1 week to acclimate to the facility and were handled for a minimum of 4 days before experimental procedures began. All rats initially participated in spontaneous  into the CA3 subregion of the hippocampus (see below). After surgery, rats were given 1 week to recover and then placed on a restricted feeding protocol to encourage appetitive behaviors. During food restriction, each rat was given 25 ± 5 g moist chow  once daily and drinking water was provided In order to identify lateral entorhinal cortical (LEC) cells with afferent projections to CA3, all rats received bilateral injections of the retrograde tracer cholera toxin subunit B (recombinant) Alexa Fluor 594  . Rats were then shaped to alternate between the start area and choice platform. For these sessions, one of the two food wells on the choice platform was baited with a piece of Froot Loop. Rats were required to leave the start area, traverse the length of the arm, retrieve the food reward, and return to the start area where a second food reward was provided. After shaping, rats were tested on an unrelated object discrimination task  recorded each exploration epoch using a custom software interface . The data were later processed offline using custom written software in MATLAB , to obtain the total distance moved and the proportion of the environment explored. Immediately following the second 5 min foraging epoch, rats were anesthetized in a glass bell jar with isoflurane vapors and decapitated with a rodent guillotine. Brains were rapidly extracted, hemisected, and flash frozen in chilled isopentane (~ −50°C). Brains were stored at −80°C until cryosectioning. In addition to the rats that randomly foraged, one young and one aged rat were sacrificed directly from the home cage as negative caged controls (Aged-CC and Young-CC). One hemisphere was processed for each rat and selection of the left or right hemisphere was counterbalanced across rats and age groups.Arc cDNA . Tissue was incubated with the probe overnight and Arc positive cells were detected with anti-digoxigenin-HRP conjugate . Cyanine-3  was used to visualize labeled cells and nuclei were counterstained with DAPI (ThermoFisher Scientific). Z-stack images with 1 μm optical sections were collected by fluorescence microscopy . For each rat, 6 images were taken from each region of interest  across 3–4 slides. All hippocampal CA3 images were collected between coordinates 3.0 and 4.0 mm posterior to bregma. All LEC images were collected between coordinates 5.6 and 6.5 mm posterior to bregma , and arranged on a slide so that tissue from both age groups and a caged control (sacrificed directly from the home cage) was represented on a single slide. During slicing all tissue was thaw-mounted on Superfrost Plus slides  and stored at −80°C until FISH processing. Every 10th section was immediately DAPI stained to localize CTB injection sites and labeled projection neurons, and to ensure that the FISH procedures did not degrade the CTB signal. Twenty-four hours prior to FISH, tissue was moved to a −20°C freezer overnight to prepare for thawing. FISH was performed as previously described  with a value that can be used to compare activity patterns across different brain regions. The similarity score takes these four measured cell-labeling values and reduces them to a single value. Similarity scores were calculated for each rat that performed two epochs of behavior prior to sacrifice. A value of 0 indicates that two statistically independent cell populations were activated during the two epochs. A value of 1 indicates that an identical cell population was activated during the two epochs of behavior, while a value of -1 indicates that no cells were activated during both the first and second epochs of behavior. The similarity score was calculated as previously described  was quantified .All statistics were run on the means for individual rats, such that sample size reflects the number of rats in each age group. When main effects were significant at the T(18) = 0.92, p = 0.37]. These data indicate that there was not an effect of age on the rats' abilities to learn to displace an object to retrieve a food reward, and to associate a particular object with a reward when the two objects to be discriminated were distinct . Following discrimination testing with unrelated objects, rats completed 10 days of discrimination testing with LEGO® objects that shared 87% feature overlap . While this may appear counter to prior research , with all rats making fewer errors on the unrelated object discrimination compared to the LEGO® discrimination. The difference in % correct responses between unrelated and LEGO® object discriminations did not significantly vary with age .Once at an optimal body condition score was obtained (see above), rats were initially trained on an unrelated object discrimination problem in order to habituate them to the procedural aspects of object discrimination testing. All rats received 2 days of training on unrelated object discrimination Figure . Mean pep < 0.05; one-sample Kolmogorov–Smirnov test). K-means clustering identified two clusters, one with a mean of 56.5 and another with a mean of 90.2. Seven aged rats were classified into the poor performer cluster and 4 aged rats in the good performer cluster. These animals were designated aged-poor performers (A-poor) and age-good performers (A-good), respectively. For the young rats, 4 were classified into the poor performer (Y-poor) cluster and 5 in the good performer (Y-good) cluster. This bimodal distribution of performances in both young and aged rats affords the ability to determine if the same neurobiological variables can explain behavioral differences across young and aged animals.Figure p < 0.05; Kruskal–Wallis Test]. This was due to all groups performing similarly on the unrelated discrimination problem , while the Y-poor and the A-poor groups had significantly fewer correct trials on the similar object discrimination compared to the other two groups . Importantly, there was not a significant correlation between individual rats' performance on the unrelated and similar object discrimination tasks . Therefore, the total amount of novel area explored was similar across all groups.At the conclusion of discrimination testing, rats randomly foraged for food rewards in two different novel arenas placed in distinct environments during two 5-min epochs. During each 5-min epoch, rats voluntarily ambulated for small pieces of Froot Loop cereal. In order to provide orthogonal conditions, the rooms, foraging arenas and experimental handlers differed between epochs 1 and 2. A 20-min delay was imposed between each epoch in which the rat remained in their home cage. Figure p > 0.1; One-sample Kolmogorov–Smirnov Test). When the distance traveled within each epoch was compared across arenas, there was a significant effect of epoch . This was due to the rats walking a greater distance in the second epoch, likely because they became accustomed to the random foraging procedures. There was also a significant effect of group on distance traveled . Post-hoc analyses indicated that the good and poor performing young rats traversed a similar distance , as did the A-good and A-poor rats (p = 0.71). In contrast, the A-good rats traversed significantly fewer meters compared to both groups of young rats (p < 0.05 for both comparisons). There was not a significant interaction effect of group and distance traversed , indicating that the aged rats moved less in both epochs compared to young. This was likely due to the slower ambulation velocities typically observed with age. This factor was considered with respect to the levels of Arc expression (see below). Notably, while the aged rats moved slower, they did explore similar portions of the arenas compared to the young rats.The mean distance traveled Figure  in epochT(18) = 0.55, p = 0.52]. Cell number also did not vary significantly between any of the behavioral groups , which is consistent with stereological counts showing no loss of CA3 neurons with age  and counterstained with DAPI (blue). The white rectangles indicate the distal and proximal regions of CA3 from which z-stack images were acquired at 40X magnification. When the total % of CA3 cells that expressed Arc  = 0.34, p = 0.56], which is consistent with a previous report  = 3.16, p < 0.05]. Two planned orthogonal contrasts were run in order to test for specific differences between groups. A simple contrast in which the A-poor rats were compared to every other group indicated that these animals had significantly more CA3 neurons that expressed Arc relative to the A-good and Y-good performing animals . There was also a non-significant trend for the A-poor group to have more Arc-positive cells than the Y-poor performers . In contrast to the A-poor group, the Y-poor performers did not have significantly different percentages of Arc positive cells compared to either the Y-good performers or A-good group (p > 0.64 for both comparisons). These data suggest that enhanced activity in CA3 can explain behavioral variability on a discrimination task in aged animals, but not in young animals.The average number of cells captured per image within CA3 was 51.15 for the young rats and 48.21 for the aged rats, which was not statistically different  or region . There was, however, a significant effect of group  with the A-poor rats having significantly more cells expressing Arc compared to the other groups . None of the interactions between factors reached statistical significance . These data provide further support that the A-poor rats had more cells in CA3 that expressed Arc during behavior. Importantly, there was not a significant correlation between distance traversed in epoch 1 and epoch 2 and the percent of cells that were Arc positive in either distal , or proximal CA3 . These data suggest that group differences in total distance traveled could not account for the increased proportion of CA3 cells expressing Arc in the A-poor performing rats.When the percent of neurons expressing l Figure  and proxl Figure  CA3 withF = 11.15, p < 0.01]. Behavioral group did not have a significant effect on similarity score , and did not significantly interact with position on the transverse axis . These data indicate that when rats explored two distinct environments that were both novel, all groups showed recruitment of distinct neural populations in CA3.The degree to which neuronal ensembles activated during two distinct epochs of behavior are uncorrelated can be quantified by calculating a similarity score  or proximal CA3 . Furthermore, the deviation from expected activation was not significantly different between the four behavioral groups in either distal  or proximal CA3 . These data indicate that under the behavioral parameters of the current experiment there was not a detectable difference in the probability that a CA3 neuron would be active across multiple environments between young and aged rats.Figure l Figure  and proxl Figure . ObserveT(16) = 1.0, p = 0.33]. Of these cells, the average number of CTB positive neurons was 8.26 for the young rats and 8.20 for the aged rats, which was also not significantly different . Total LEC cell number  and CTB positive cell number  also did not vary significantly between any of the behavioral groups . These data are consistent with stereological counts showing no loss of LEC neurons with age  was injected into CA3 of all rats 21 days before sacrifice. Layer II LEC neurons that were positively labeled for CTB were identified as projecting to CA3 Figure . The aveArc was significantly higher when the LEC neuron population was restricted to those neurons that project to CA3 compared to all layer II LEC cells . The increased likelihood of a cell being active in projection neurons did not significantly interact with behavioral group . Moreover, when the total percent of all LEC cells that expressed Arc was compared across the different behavioral groups, there were no significant differences across groups . However, when the percent of neurons expressing Arc was compared across epochs for all layer II LEC neurons  = 4.53, p < 0.05] and for the LEC to CA3 projection neurons  such that the proportion of Arc positive LEC neurons was higher in the first epoch relative to the second. There was also a significant interaction of behavioral group and epoch for all LEC neurons , and for CA3 projecting LEC neurons . Post-hoc analysis indicated that this was due to the A-poor group having a significantly higher percent of LEC cells expressing Arc compared to the other groups during epoch 1 , but not during epoch 2 . The same pattern in the data were observed for all layer II LEC cells when the analysis was restricted to CA3 projecting neurons.The percent of cells that expressed s Figure  and for s Figure  with repArc in all layer II LEC neurons and in the CA3 projecting neurons  = 28.93, p < 0.001]. Specifically, LEC neurons that project to CA3 are significantly more likely to have non-overlapping populations of neural activity between two epochs of exploring different novel environments than the general population of layer II LEC neurons. This did not significantly interact with behavioral group  indicating that, similar to the A-good and young animals, A-poor rats had a new population of cells active when the environment changed.To examine the extent that LEC neurons update their activity patterns when the environment changes, a similarity score was calculated from the distribution of s Figure . A repeaArc positive cells for all LEC cells . This suggests that more LEC neurons are likely to be activated during both epochs of exploration than what is expected by chance, which is consistent with a previous report . This deviation from expectation did not significantly differ between the four behavioral groups . Together these data indicate that CA3-projecting LEC neurons have different activity dynamics than the larger population of LEC neurons, which favor the recruitment of orthogonal neural ensembles across different behavioral episodes.Figure s Figure  and for s Figure . When alArc in CA3 was significantly more sparse compared to LEC neurons that project to CA3 , which did not interact significantly with behavioral group . When the similarity score was used to compare the extent that CA3 cells and CA3-projecting LEC cells have independent populations of active neurons during the two different epochs of exploration, there was not a significant effect of region on similarity score . These data suggest that the probability of cells being active in both environments did not differ between LEC projection neurons and CA3. Moreover, for the young rats, the similarity score for LEC projection neurons was negatively correlated with the similarity score for proximal CA3 neurons , and positively correlated with the similarity score for distal CA3 neurons . In both cases, however, this effect appeared to be carried by one outlier and when that data point was removed, these relationships were no longer significant (p > 0.3 in both cases). One difficulty with examining correlations between CA3 and LEC similarity scores is that they cluster between 0 and 0.1, which does not offer parametric space for detecting significant relationships. Future experiments will need to examine the possibility of this relationship using behavior procedures that lead to more variable amounts of overlap between active neuronal ensembles. In the aged rats, there was not a significant relationship between similarity scores calculated from projection neurons in LEC and proximal  or distal CA3 .The total percent of cells positive for Arc mRNA. The original hypothesis was that those animals with the greatest discrimination impairments would be the same animals in which CA3 ensembles would not remap across environments. We also predicted that this would be related to rigid activity patterns in the LEC neurons that project to CA3. Surprisingly, all rats showed orthogonal ensembles of active cells in CA3 and LEC across the two novel environments.The current experiments were initially designed to measure the extent to which the inability of aged CA3 place fields to update in a new environment could be accounted for by sensory discrimination deficits. Aged and young rats were pre-characterized on a LEGO® object discrimination task over 10 days of testing to quantify sensory discrimination abilities Figures . After dArc following two epochs of random foraging in different novel environments. In contrast, the young rats that performed poorly on the LEGO object discrimination task had comparable percentages of cells that were positive for Arc to the young rats that were good performers on the task (Figure Importantly, in both age groups, there was a subset of rats that did not learn to discriminate between two perceptually similar objects by day 10. A novel finding from this work is that only the aged-impaired rats had a larger percent of principal cells in both CA3 and LEC that were positive for the immediate-early gene k Figure . Thus, dk Figure , 2011. FThe observation that aged, but not young, poor performing rats have a higher proportion of active CA3 cells during behavior leaves the question as to whether the poor-performing young rats are expressing a behavioral phenotype that predicts age-related impairments. Longitudinal studies have shown that the young animals with more impulsive traits are more likely to develop cognitive deficits in advanced age (Dellu-Hagedorn et al., Wilson et al.  were theConsistent with the electrophysiological data from animal models, high-resolution human fMRI data have reported a higher BOLD signal in the dentate gyrus/CA3 in non-demented elderly subjects (Yassa et al., Arc in A-poor performing rats is consistent with reports of CA3 hyperactivity, unlike previous studies (Wilson et al., While the higher percentages of cells that where positive for the neural activity-dependent immediate-early gene Another interesting finding regarding the overlapping activity patterns between the two different environments was the decreased similarity across epochs in distal compared to proximal CA3. Several reports have documented distinct activity dynamics along the transverse axis of CA3 such that proximal CA3 is more likely to pattern separate than the more distal portions in situation with cue conflict or overlapping input patterns (Marrone et al., While the aged LEC neurons showed distinct neural populations that were active between the two environments across all behavioral groups, the aged-poor rats had a higher percent of LEC neurons that were active during the first epoch, relative to the other groups Figure . BecauseFinally, this study investigated the allocation of cell activity across environments. As described previously (Witharana et al., AM and SB designed the experiment, analyzed the data, and wrote the paper. SJ, AH, KL, JR, DC, KF, and JM assisted in collecting and analyzing data. BC provided surgical training and data analysis support.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Plasmodium falciparum resistant strains. We investigated resistance to artemisinin-based combination therapies currently in use in Democratic Republic of Congo by surveying molecular polymorphisms in three genes: pfcrt, pfmdr1 and pfk13 to explore possible emergence of amodiaquine, lumefantrine or artemisinin resistance in Democratic Republic of Congo. This study essentially revealed that resistance to chloroquine is still decreasing while polymorphism related to amodiaquine resistance seems to be not present in Democratic Republic of Congo, that three samples, located in the east of the country, harbor Pfmdr1 amplification and that none of the mutations found in South-East Asia correlated with artemisinine resistance have been found in Democratic Republic of Congo. But new mutations have been identified, especially the M476K, occurred in the same position that the M476I previously identified in the F32-ART strain, strongly resistant to artemisinine. Antimalarial first-line treatments currently in use in Democratic Republic of Congo are not associated with emergence of molecular markers of resistance.Malaria is a major public health problem in the Democratic Republic of Congo. Despite progress achieved over the past decade in the fight against malaria, further efforts have to be done such as in the surveillance and the containment of  In the Democratic Republic of Congo (DRC) malaria is still a major public health problem. Interventions conducted the last ten years led to reduce malaria related morbidity-mortality , but furPlasmodium falciparum resistant strains. Resistance, that could be defined as the ability of a parasite strain to survive or multiply in the presence of drug concentrations that normally kill parasites of the same species or prevent their multiplication [Efforts must be strengthened in many topics, such as surveillance and containment of lication , is a phlication . In resplication . CurrentIn DRC, two ACTs have been accepted as first-line treatment by the National Malaria Control Program (NMCP): Artesunate-Amodiaquine in 2005 followed by Artemether-Lumefantrine in 2010. Both combinations are simultaneously in use in the country.Resistance to previous antimalarials has led to an increase of malaria mortality from 1980 to 2004 , an incrin vivo treatment trials or in vitro drug susceptibility testing to detect drug-resistant strains as they allow analyzing large sample and assessing resistance to many antimalarial drugs simultaneously [Monitoring parasite resistance to antimalarial drugs is mandatory in malaria control strategies. Molecular markers are a good alternative to aneously . Unfortuaneously .Plasmodium falciparum chloroquine-resistance transporter (pfcrt) gene is the key element of chloroquine resistance [Kelch 13 gene  and artemisinin resistance [Plasmodium falciparum multidrug resistance 1 (pfmdr1) gene and increase of its copy number have been related to resistance to many monotherapies [Some molecular markers associated with malaria resistance have been clearly described. The K76T mutation occurring on the sistance  and the sistance . Moreovesistance . Mutatioherapies –20 but aherapies , 22.pfcrt mutants in Kinshasa [pfcrt, pfmdr1 and pfk13 to explore possible emergence of amodiaquine, lumefantrine or artemisinin resistance in DRC.In previous studies, we have detected a high prevalence of Kinshasa  so in thThe protocol and the informed consent received the ethical approbation from the Ministry of Public Health of the DRC and from the Institutional Committee of the Faculty of Medicine, University of Kinshasa. All the participants involved in the study (or the parents/guardians of children) provided a written consent.We conducted this study in six areas with different dynamics of transmission: Bolenge, Luzizila and Mweka in the equatorial facies; Punia and Kapolowe in the tropical facies and Butembo in the mountain facies. Malaria transmission is perennial in the equatorial and tropical facies but seasonal in the mountain one. In each site, one hundred individual has been randomly selected in a household survey . The survey was conducted between March and November 2014.® DNA mini kit  as previously described [For each individual, blood samples were collected from finger prick and DNA was extracted by using the QiaAmpescribed .P. falciparum + P. ovale and P. malariae + P. vivax) was run to detect Plasmodium species [®) in the Clinical microbiology Unit of the University Hospital of Liege, Belgium. P. falciparum positive samples were stored at −20°C for further molecular analysis.One real-time PCR consisting in two duplex reactions (identifying  species  on a Ligpfmdr1 detection and another couple of primers with a VIC-labeled probe for β-tubullin detection [®) in the presence of one single copy control reference strain 3D7. The results were analyzed by the comparative ΔΔCt method. Parasites were considered to have an amplified pfmdr1 gene if copy number was > 1.5 [A relative quantification multiplex real-time PCR was run by using a couple of primers plus a FAM-labelled probe for etection . Assays as > 1.5 .pfcrt gene containing the region of interest followed by sequencing of amplicons, as described in a previous work [A conventional PCR was run to amplify an approximately 152 pb fragment on the ous work . Both 3D® kit  and then sequenced jointly in the GIGA centre of University of Liege, Belgium and in the Molecular biology platform of the University Hospital of Liege, Belgium using a 3130xl DNA sequencer .Another conventional PCR was run by using primers recently described by Ariey et al.  to ampli® Software Ver. 5.4.5  and the online BLASTx tool .The K13-propeller SNPs were analyzed by comparing with the reference 3D7 strain (PF3D7_1343700) using SequencherP. falciparum, among which 6 (2.14%) were mixed infections . Distribution of these prevalences by area and by age group has been described in a previous published study [Out of the 580 samples collected over the six geographic sites, 280 (48.2%) were PCR-positive to ed study . All resPfmdr1 analysis was successful for all P. falciparum positive samples. Only three samples (1.07%), all found in Butembo (Nord-Kivu province) have a copy number amplification beyond 1.5.One hundred and seventy-nine samples (63.9%) harbored the 76T mutation among which two had the relatively rare CVMNT haplotype (in Mweka and Kapolowe) and the rest got the CVIET one.On the 280 samples analyzed, sequencing was correctly done for 261 samples. We identified 9 samples (3.4%) with mutations in the propeller domain of the K13 among which 3 mutations previously described  and 3 new mutations .Since the Congolese NMCP introduced ACT as first-line treatment in 2005, whatever some local studies have assessed ACT efficacy, only one national survey, conducted by the NMCP, has been performed to assess malaria first-line treatment efficacy. But results of this study have not yet been published.pfmdr1 copy number and all of these samples are from Butembo, in the east of the country. This is the first time that amplification of pfmdr1 gene copy number is assessed in DRC. Our results are similar to those reported from African samples by Uhlemann et al. in Gabon [pfmdr1 gene copy number was detected. That seems to be different than in South-east Asia where amplification of Pfmdr1 copy number is frequently high [P. falciparum strains with pfmdr1 amplification in African samples [pfmdr1 copy number [In this study, we reported only 1% 3/280) of the samples that have increased 0 of the in Gabon  or Gadalin Gabon  in Sudantly high , 26, 30. samples . One othy number , was widpfmdr1 copy number has been linked with treatment failure (or reduced sensitivity) to some ACT [pfmdr1 copy number in the East of the DRC emphasizes the importance of maintaining regular monitoring.Increased some ACT , 29, 32.pfmdr1 resistance-based is maybe emerging in the East of the country before to expand to the rest of the country. Before the present work, only one study assessed pfmdr1 polymorphism in DRC but by exploring the N86Y mutation [As previously observed for Sulfadoxine-Pyrimethamine or chloroquine, mutation .in vivo and in vitro amodiaquine resistance [Despite the fact that prevalence of the K76T mutation (related to chloroquine-resistance) is still in a high level in our results (65.7%) and that a cross resistance has been described between chloroquine and amodiaquine , the SVMsistance , has notsistance –40. It spfk13 gene, six different mutations in the propeller domain were detected into nine samples (3.2%). Two of these mutations have been previously described in other African countries. The S522C mutation was isolated in the present study in a sample from Butembo and has been previously reported in Uganda [After analysis of the n Uganda , which iOn the other hand, we found the V520A mutation in two sites relatively distant (Luzizila and Mweka). Our results are similar to those reported by Taylor et al. who found this mutation in DRC too, in the same geographic area than us. In the results provided by Taylor et al. in 2015, this mutation appears to be the most common in African parasites as it has been reported in several African countries  . One musSurprisingly, the F495L mutation that we found in Mweka was described for the first time in samples from the China Myanmar border  then in pfk13 gene . The M476K mutation could be of a particular interest because one mutation on this position, the M476I, that appeared in vitro after artemisinin pressure in an African line from Tanzania (F32-ART) [We also found three undescribed mutations on the F32-ART) , 45. ThiF32-ART) . UnfortuThe newly reported E509D and N523T mutations are not related or close to resistant polymorphisms described in Asia.None of the mutations clearly correlated to increased parasite clearance time in Asian samples have been found in Africa yet.P. falciparum genes related to drug resistance. None of the mutations clearly associated to ACT resistance have been found in this study.The data reported in this study reports the occurrence of some polymorphisms onto pfk13 gene highlights the importance of a continuous monitoring. We unfortunately have not assessed in vitro susceptibility of the isolates with these new mutations.As in the rest of Africa, resistance to artemisinin seems not to be yet present there. DRC is one of the rare countries that have officially adopted multiple first-line treatment in its policy. This could provide a protective effect to the emergence of resistant strains but discovery of new mutations on the S1 Table(DOCX)Click here for additional data file.


Although the diagnosis of prolactinoma is often straightforward and the treatment strategy has been well defined in recent guidelines, several challenging issues persist in their management. The differential diagnosis of a large pituitary tumour with moderately elevated prolactin (PRL) concentrations is sometimes difficult, and prolonged treatment with a dopamine agonist may be inappropriate when the diagnosis of a prolactinoma is not sufficiently well substantiated. Also, timely withdrawal of dopamine agonist treatment and the remaining indications of transsphenoidal surgery are still matters of debate. Last but not least, the management of resistant or aggressive prolactinomas remains a challenge for the clinician, especially when they occur in young patients. This affection has a large female predominance and a median age of 30 years at diagnosis.diagnosis of prolactinoma is usually based on the concomitant observations of a persistent hyperprolactinaemia and a pituitary adenoma at magnetic resonance imaging (MRI) with a good correlation between hormone levels and tumour size.1 It is rarely confirmed by immunocytochemistry of the tumour, as most prolactinomas are never operated. Macroprolactinomas can usually be recognised with a high degree of confidence when prolactin (PRL) concentrations are above 200 μg/l 5. In patients with histologically confirmed non-functioning pituitary macroadenoma and stalk compression, PRL concentrations usually remain lower than 150 μg/l.6 In cases of doubt , a 3- to 6-month trial with a dopamine agonist (DA) may be helpful, as most prolactinomas will show some degree of shrinkage under medical therapy. A thyrotropin-releasing hormone (TRH) stimulation test usually is not helpful in such circumstances.The 3 Noticeably, most microprolactinomas will be symptomatic, readily visible on dedicated MRI as a lateral nodule with a different T1 or T2 intensity than normal pituitary tissue, and exhibit PRL concentrations >40 μg/l . The absence of one or more of these criteria is still compatible with the diagnosis, but the clinician must be aware of other aetiologies and consider surveillance or early withdrawal of DA treatment before embarking the patient on long-term therapy. Discordance between excellent hormonal control under DA therapy and ongoing tumoral expansion must also lead to re-evaluation of the diagnosis.It may be even more difficult to formally confirm the diagnosis of a microprolactinoma. Symptoms of hyperprolactinaemia are not specific of a tumoral origin, MRI findings may be ambiguous, non-functional pituitary incidentalomas are frequent and several other causes of moderate hyperprolactinaemia must be ruled out. Among them, drug-induced hyperprolactinaemia is a common condition (see 7 for review), and assessment for the presence of macroprolactin is also highly recommended in patients with asymptomatic hyperprolactinaemia.treatment of prolactinomas with a DA is the cornerstone of therapy, and cabergoline (CAB) is the first choice due to its high efficacy and good tolerability profile.4 Even in the case of very large adenomas with suprasellar extension, CAB induces rapid tumour shrinkage and visual field improvement in 80–90% of patients.5 One remaining factor is to decide when treatment can be safely withdrawn. Discontinuation of DA therapy is indeed possible with reasonably good chances of remission in well-defined conditions:8 (a) the patient has been continuously treated for at least 2 to 3 years (probably more for macroprolactinomas); (b) a low PRL concentration has been obtained with a low dose of DA (<0.5 mg/week of CAB); (c) a disappearance or a more than 50 % reduction in the maximal tumoral diameter has been observed; and (d) there is no cavernous sinus invasion. When such criteria are met, prolonged remission is observed in about one-third of the patients, more often after the use of CAB in the context of microprolactinomas (50 %) than with bromocriptine or in macroprolactinomas.8 These patients require, however, longterm surveillance, and a loss of follow-up with later resurgence of the prolactinoma is a potential risk of such strategy. It is also possible to discontinue dopaminergic therapy after menopause3 or after one or more pregnancies, which seem to increase the likelihood of remission.9Medical 3 Besides these classic indications and some acute complications, such as apoplexy or cerebrospinal fluid (CSF) leakage, new indications have emerged, such as young patients with a high likelihood of complete tumour resection who do not wish to take prolonged medical treatment10 or patients who require high doses of CAB, in whom surgical debulking may significantly improve post-operative hormonal control.11 It is essential that the surgical procedure be performed by an experienced pituitary neurosurgeon. In such centres, immediate post-operative remission rates of 70–90 % have been reported for microprolactinomas and of 30-50 % for macroprolactinomas (reviewed in 12).Neurosurgical treatment of prolactinomas is less effective than medical therapy, and recurrence of hyperprolactinaemia is frequent (10–50 % of patients). Nevertheless, transsphenoidal surgery should be considered in symptomatic patients who cannot tolerate any of the currently available DAs or who are not responsive to maximally tolerated doses of DAs.4 This resistance is rare in microadenomas, more frequent in cases of macroprolactinomas (3–5 %) and quite characteristic of invasive tumours.2 Although a decreased expression of D2 receptor has been evidenced in resistant prolactinomas, the mechanisms are still not completely understood.13Resistance to DA treatment is another therapeutic challenge, being defined by a failure to achieve normal PRL levels on maximally tolerated doses of DAs and/or failure to achieve a 50 % reduction in tumour size.13 If the patient is treated with another DA, it is recommended to switch to CAB. About 70–80% of patients resistant to bromocriptine may indeed achieve PRL normalisation on CAB.3 Next, standard doses of CAB may be increased stepwise to maximal tolerable doses. In a Japanese study,14 increasing the CAB dose up to 12 mg/week allowed the overcoming of DA resistance in a few patients, but perhaps at the price of long-term undesirable side effects. Therefore, in the absence of any intolerable symptoms or emergency situation, we rather recommend keeping the maximal dose at 3.5 mg/week, which may, in turn, lead to hormonal control in half of the cases after 15 to 72 months.2 Finally, the resistant prolactinoma is also a valuable indication for transsphenoidal neurosurgery, aiming at large tumoral debulking and improved postoperative medical control.11 Irradiation must be considered only in the rare patients who fail surgical treatment and harbour aggressive prolactinomas.3 It may require up to 20 years for maximal effects to be achieved, and normalisation of hyperprolactinaemia occurs in only one-third of cases4. Finally, in aggressive prolactinomas or PRL-secreting carcinomas, a last therapeutic option may be the use of temozolomide, an orally administered alkylating agent, which might reduce PRL hypersecretion and control tumour growth in about 50 % of cases.16Several therapeutic options may be considered in cases of DA resistance.17 long-term echocardiographic surveillance  is indicated in patients who chronically need higher doses of DAs. It is also important to keep in mind that true resistance of prolactinomas to adequate medical treatment is often associated with a more aggressive behaviour of the tumour. These patients must therefore be followed more closely in a specialised centre.Although the risk of restrictive cardiac valve disease seems to be very low at conventional doses (≤1.0 mg/week) of CAB,