3 ± 11 4

years) and 1378 healthy controls (54 0% female;

3 ± 11.4

years) and 1378 healthy controls (54.0% female; mean age 51.1 ± 17.0 years) for which genotype data at the four FEZ1 SNPs were available ( Table S1A). No significant results were detected on susceptibility to schizophrenia for each of the four FEZ1 SNPs, which is consistent with the result from the ZHH cohort ( Table S1A). The platform used to genotype GAIN (Affymetrix 6.0 chip) did not include the DISC1 Ser704Cys marker but has a perfect proxy for this SNP (rs1754605; r2 = 1.0). We then performed a backward check details stepwise regression to test for an interaction between the proxy SNP for DISC1 Ser704Cys and FEZ1 rs12224788 ( Figure 6C). As this approach was to serve as a replication of the findings in the ZHH data set, we included only the FEZ1 SNP with statistical evidence of epistasis (FEZ1 rs12224788) in the GAIN sample regression model ( Table S1B). Variables retained in the best fit model included FEZ1 genotype (Beta = 0.72; p = 0.041), DISC1 genotype (Beta = 0.53; p = 0.044), and the interaction term FEZ1 × DISC1 (Beta = −0.45; p = 0.039). While the significant interaction is consistent with results from the ZHH data set, the Beta term is negative, suggesting a somewhat different pattern of

interaction in the GAIN sample as compared with the ZHH sample. Specifically, χ2 analyses revealed only a trend-level association for the C allele at FEZ1 this website rs12224788 in DISC1 Ser homozygotes (χ2 = 1.53; df = 1; p = 0.12; OR = 1.2) and a significant association for the FEZ1 GG genotype in the context of a DISC1 Cys background (χ2 = 2.83; df = 1; p = 0.05; OR = 0.77; Figure 6B). While not identical, this pattern of risk association related to the interaction is consistent with that found out in the ZHH sample. We also performed a series of χ2 tests in the same way to test for a potential interaction between our NDEL1 risk SNP (rs1391768) ( Burdick et al., 2008) and each of the four FEZ1 SNPs using the ZHH sample. We carried out four separate χ2

analyses with one for each FEZ1 SNP, while conditioning the sample on NDEL1 rs1391768 status. The results from these analyses provided no significant evidence of interaction among these four FEZ1 SNPs and NDEL1 rs1391768 (all p > 0.10; Figure S6D and data not shown). Taken together, these genetic interaction results from clinical cohorts mirror the biochemical and cell biological findings of a synergistic interaction between FEZ1 and DISC1, but not between FEZ1 and NDEL1, in regulating neuronal development in the animal model. Cumulative evidence supports a significant neurodevelopmental contribution to the pathophysiology of schizophrenia and other major mental disorders (Lewis and Levitt, 2002, Rapoport et al., 2005 and Weinberger, 1987), yet underlying molecular mechanisms are far from clear. DISC1 has emerged as a general risk factor for schizophrenia, schizoaffective disorder, bipolar disorder, major depression, autism, and Asperger syndrome (Chubb et al., 2008 and Muir et al., 2008).

Deprivation did not alter integrated threshold Ge (calculated fro

Deprivation did not alter integrated threshold Ge (calculated from response onset to each cell’s mean AZD2014 supplier spike latency) or peak, indicating that the amount of excitatory drive necessary to elicit a spike from Vrest was unaltered (n = 8 sham, n= 6 deprived) (Figure 5D and Figure S2). Together, these results indicate that FS cell intrinsic excitability is essentially unaltered after deprivation. However, deprivation did increase onset latency of threshold Ge onto L2/3 FS cells (sham deprived: 3.3 ± 0.3 ms; deprived: 4.4 ± 0.2 ms; p < 0.05), with a corresponding increase in

evoked spike latency (7.8 ± 0.5 ms versus 11.1 ± 1.4 ms; p < 0.05) (Figure S2). In L4 of visual cortex, sensory deprivation has been reported to enhance inhibition by potentiation of inhibitory FS→PYR synapses (Maffei et al., 2006). To test whether L2/3 FS→PYR synapses are also altered by whisker deprivation, we measured connectivity rate and synapse properties for unitary inhibitory connections from L2/3 FS cells to PYR cells (L2/3 FS→PYR synapses) in D columns from deprived and

sham-deprived rats (Figure 6A). Cells were www.selleckchem.com/products/SNS-032.html patched with a low chloride internal (ECl = −88mV) to increase the size of hyperpolarizing unitary IPSPs (uIPSPs) (Figure 6B). FS spikes were elicited by current injection, and connected FS→PYR pairs were identified by a statistically significant uIPSP amplitude compared to a prespike baseline period (20–40 sweeps; post-PYR cell Vm = −50mV; paired sign rank test; p < 0.05). The L2/3 FS→PYR connection MRIP rate was greater in deprived columns (22/28 pairs

connected, 78.6% connection rate [95% confidence interval 61%–93%]) versus sham-deprived columns (21/45 pairs connected, 46.7% [31%–60%]; p < 0.01; rank-sum test). Intersoma distance was identical for these connected pairs (deprived: 57 ± 5 μm; sham deprived: 56 ± 3 μm). FS→PYR uIPSP amplitude for connected pairs was also greater in deprived (−1.59 ± 0.23mV; n = 21 pairs, measured at Vm = −50mV) than in sham-deprived columns (−0.69 ± 0.12mV; n = 20; p < 0.01; t test; one pair in each condition excluded because of low Rin). uIPSP slope was similarly increased (deprived: −0.27 ± 0.05mV/ms; sham deprived: −0.12 ± 0.02mV/ms; p < 0.01) (Figures 6B–6D). This increase in uIPSP synapse strength and connection rate was associated with a decrease in failure rate (deprived: 16.3% [8%–30%]; sham deprived: 36.8% [22%–52%]; p < 0.04; rank-sum test) and coefficient of variation (deprived: 0.27 [0.22–0.37]; sham deprived: 0.40 [0.30–0.69]; p < 0.05; rank-sum test). Deprivation did not alter short-term plasticity during trains of five presynaptic spikes (50 ms isi) or uIPSP kinetics (Figures 6E and 6F). Together, these results suggest that deprivation strengthens uIPSPs by increasing the number of synapses or release sites.

The main limitation of this approach is that transgene


The main limitation of this approach is that transgene

expression often does not fully recapitulate that of the endogenous gene and varies among transgenic lines. Given current knowledge about mammalian gene regulation and chromatin biology, this should perhaps come as no surprise. First, cis regulatory elements (enhancers, repressors, insulators) are often very distant from the transcription start site Selleckchem Y-27632 ( Kapranov et al., 2007); thus, even BAC constructs often do not contain the full complements of regulatory elements of the gene of interest. Second, because cis-regulatory elements can act at a very long distance ( Bulger and Groudine, 2011 and Heintzman and Ren, 2009), enhancers and repressors near the transgene integration site (but that are unrelated to the promoter elements in the transgene) can influence transcription, leading to ectopic or suppressed expression. Third, different transgenic lines will have different expression patterns due to differential enhancer/repressor influences at different genomic integration sites. Fourth, transgenes inserted into a foreign chromatin environment can be silenced or epigenetically altered in unpredictable ways. Thus, the challenges often associated with the transgenic strategy are the uncertainty of the targeted

neurons and the effort necessary to ascertain their identity and property. Here, we have used the gene knockin strategy to target GABAergic neurons. Cre cassettes are inserted by homologous recombination at endogenous gene loci, which are embedded in their native chromatin Selleckchem 5 FU environment with largely intact regulatory elements. The main advantage of this strategy is

that Cre expression precisely and reliably recapitulates the targeted endogenous gene. Indeed, after extensive characterization we found that recombination patterns in almost all the PAK6 GABA Cre drivers often perfectly match the spatial and temporal pattern of the endogenous gene expression. The disadvantages of gene targeting approach include: (1) the possibility of altering the expression of the targeted gene, even when a bicistronic cassette (e.g., ires or T2A) is inserted after the targeted gene (see below); (2) the full expression pattern of a gene may include multiple cell types or brain regions; thus, in some cases the partial expression pattern may be more desirable (although this issue can sometimes be addressed by using Cre-dependent viral vectors which can be injected to defined brain regions). Extensive characterization of eight constitutive drivers indicated that this strategy is highly effective. First, Cre activities appear highly specific and largely match the expression of the targeted genes. In certain lines and brain regions, recombination patterns do deviate from that of the endogenous expression in adult brain (e.g., CCK-ires-Cre, Figure 6D).

Thus, the role of GABAergic circuits in regulating contrast polar

Thus, the role of GABAergic circuits in regulating contrast polarity sensitivity, not surround responses, is critical for linearizing responses to contrast in L2. Our results reveal a nonlinear, spatiotemporally coupled center-surround antagonistic RF structure in L2 cells that mediates different responses to dark or bright inputs of different sizes. These functional properties must affect the computations performed Selleckchem PARP inhibitor by downstream motion processing pathways and make the outputs of elementary motion detectors (EMDs) depend on the geometry and contrast of moving objects. Using pharmacological and genetic manipulations, we reveal that GABAergic circuitry, including presynaptic

inhibition via GABARs on photoreceptors, mediates lateral antagonistic effects on L2. Moreover, these circuits are required for L2 to respond strongly to decrements, enabling the downstream circuits to become specialized to detect moving dark edges. Remarkably, our detailed characterization of L2 reveals that many visual processing properties are shared with first-order interneurons in the vertebrate retina. These strikingly similar computational properties arise via distinct molecular mechanisms, arguing strongly for evolutionary convergence. selleck inhibitor The L2 RF displays an antagonistic center-surround

organization over space (Figures 1 and 2), consistent with electrophysiological studies in larger

Diptera (Dubs, 1982; Laughlin and Osorio, 1989). The RF center has a radius of 3°–5°, while the surround peaks approximately 10° away from the center and persists as far as 15° or more away. Importantly, this spatial RF is nonlinear. Center responses dominate surround antagonism such that responses to surround stimulation alone are stronger than predicted from suppression of center responses by surround inputs. Furthermore, the kinetics of surround responses differ from the effect of surround inputs on center responses. Our data demonstrate Bay 11-7085 that surround antagonism affects the spatial frequency tuning of L2 outputs, reflecting higher acuity for stimuli rotating around the pitch axis compared to the yaw axis (Figures 5 and S7). Thus, fine spatial features are better captured when they are separated around this axis. Similar anisotropic center-surround RF structures were identified in LMCs of flies and other arthropods (Barlow, 1969; Arnett, 1972; Johnston and Wachtel, 1976; Mimura, 1976; Srinivasan and Dvorak, 1980; Dubs, 1982; Glantz and Bartels, 1994). We note, however, that our measurements focused on a particular dorsal and medial region of the eye. Thus, it remains possible that a distribution of spatial orientation sensitivities exists across the eye, analogous to the optic-flow sensitivity fields of motion-sensitive neurons (Weber et al., 2010).

, 1998) During recovery sleep after 12 hr of sleep deprivation,

, 1998). During recovery sleep after 12 hr of sleep deprivation, the slow wave power in the EEG and the firing of VLPO neurons both approximately double. On the other hand, the firing of VLPO neurons does not increase during prolonged wakefulness. Thus, as homeostatic sleep drive accumulates, it may influence other neurons in the brain, such as the median preoptic neurons, which provide input to the VLPO (Chou et al., 2002 and Gvilia et al., 2006), but VLPO neurons do not fire until the state transition itself (Takahashi et al., 2009). This fundamental property of VLPO neurons is consistent with their role in causing rapid and complete state transitions. A second major

influence on sleep state switching is the input from the circadian system ( Achermann and Borbély,

2003 and Borbély Selisistat ic50 and Tobler, 1985). In mammals, daily rhythms are driven by the suprachiasmatic nucleus (SCN) in the hypothalamus, a key pacemaker that influences the timing of a wide range of behaviors and physiological events. SCN neurons are intrinsically rhythmic and drive behavioral responses with a roughly 24 hr period, even in complete darkness. This rhythmicity is generated by a network of transcriptional/translational/posttranslational feedback loops that regulate the expression of clock genes ( Jin et al., 1999 and Reppert and Weaver, 2002). The clock genes are themselves transcription factors that regulate the expression of hundreds if not thousands of other genes. The activity of the SCN is entrained to the daily light-dark http://www.selleck.co.jp/products/MG132.html cycle by inputs from intrinsically photosensitive retinal ganglion cells that express the photopigment melanopsin ( Gooley et al., 2001 and Hattar for et al., 2002). Lesions of the SCN, or disruption of expression of key clock genes, results in loss of most circadian rhythms ( Bunger et al., 2000, Edgar et al., 1993 and Moore and Eichler, 1972). Surprisingly, the SCN has very little direct output to either the wake

or sleep regulatory systems (Watts et al., 1987). Instead, the bulk of its projections run into the subparaventricular zone, a region just dorsal and caudal to the SCN. Cell-body-specific lesions of the ventral subparaventricular zone nearly eliminate the circadian rhythms of sleep and wakefulness, suggesting that neurons in this region are necessary for conveying these output signals (Lu et al., 2001). However, the ventral subparaventricular neurons have few direct outputs to either wake or sleep networks. Instead, they send axons to the dorsomedial nucleus of the hypothalamus (Chou et al., 2003 and Deurveilher and Semba, 2005). The dorsomedial nucleus contains GABAergic neurons that heavily innervate the VLPO and glutamatergic neurons that innervate the lateral hypothalamic area, including the orexin neurons (Chou et al., 2003 and Thompson et al., 1996).

Last, we tested if integrin overexpression can rescue the tiling

Last, we tested if integrin overexpression can rescue the tiling defects in fry and Sin1 mutants by examining the interface between v′ada and vdaB neurons. fry1/fry6 larvae show extensive overlap of v′ada and vdaB dendritic fields ( Figure 8L), which is also caused by noncontacting dendritic crossings ( Figures 8P and Bortezomib price 8Q). Overexpression of Mys and Mew in class

IV da neurons completely rescued this phenotype ( Figures 8M and 8P). We did not observe a significant increase of heteroneuronal crossings in Sin1e03756 mutant larvae at the v′ada/vdaB interface ( Figures 8N and 8P), but found a reduction of such crossings by overexpression of Mys and Mew ( Figures 8O and 8P). It is worth noting that although integrins rescued both isoneuronal and heteroneuronal dendritic

crossing in fry mutant animals, they did not appear to rescue the overbranching phenotype ( Figures 8F and 8M), a defect associated with fry and trc that was shown to be independent of the crossing phenotype ( Emoto et al., 2004). Taken together, our results Dolutegravir price indicate that tiling mutants of the TORC2/Trc pathway cause dendritic crossings that result in overlapping dendritic fields primarily by releasing dendrites from their confinement to the 2D space specified by the ECM. Self-avoidance and tiling are fundamental mechanisms governing the proper patterning of dendritic fields. Both mechanisms involve homotypic repulsion of dendrites to ensure nonredundant coverage of dendritic fields. In principle, such repulsion could arise from contact-dependent repulsion and/or short-range diffusible repulsive signals. For Drosophila class IV da neuron, there is substantial evidence for the involvement of contact-dependent dendritic repulsion ( Hughes et al., 2007, Matthews et al., 2007 and Soba et al., 2007, this study). over For the contact-dependent dendritic repulsion to work with high fidelity, it is essential that growing dendrites encounter each other reliably when they enter a shared territory, which is only possible if they grow on the same substrate in a restricted

space such as a 2D sheet. In this study we demonstrate the dendrites of class IV da neurons mostly grow between the basal surface of the epidermal cells and the ECM secreted by the epidermis, which effectively limits the dendrites to a 2D sheet. This restriction is imposed by the interaction between neuronal integrins and epidermal cell-derived laminins in the ECM. Loss of this interaction leads to dendrites’ detachment from the ECM and increased enclosure of dendrites by epidermal cells. As a result, the dendrites are no longer restricted in a 2D space and can cross other dendrites without direct dendro-dendritic contacts. Conversely, increasing the adhesive force between dendrites and the ECM by supplying more integrins to the dendrites eliminates enclosure of dendrites in the epidermis.

After dendritic proteins are sorted into a specific vesicle popul

After dendritic proteins are sorted into a specific vesicle population, additional machinery must be recruited to ensure that these Selleck Akt inhibitor vesicles are transported only into dendrites and that they deliver their cargoes only at the correct sites. Two recent studies using novel experimental strategies have identified the kinesins and myosins

that associate preferentially with TfR-containing vesicles (Al-Bassam et al., 2012; Jenkins et al., 2012). Could AP-1A play a role in recruiting such components to dendritic vesicles? Consistent with this idea, recent work shows that the kinesin KIF13A, a known binding partner of the β subunit of AP-1 (Nakagawa et al., 2000), is implicated in the transport of TfR vesicles (Jenkins et al., 2012). Finally,

what regulates axonal protein sorting? The trafficking pathways that underlie axonal polarity remain the subject of active investigation, and no clear consensus has yet emerged concerning the nature or significance of sorting signals in axonally polarized proteins (Lasiecka et al., 2009). The strategy developed by Farías et al.—using a detailed analysis of the binding between sorting motifs and adaptors to design reagents to manipulate sorting in living cells—could also be used to elucidate the machinery that directs axonal sorting. “
“Neurons come in two flavors: Venetoclax in vivo excitatory and inhibitory. Because excitatory neurons usually outnumber inhibitory neurons in most brain regions, it’s not surprising that we know more about excitation than inhibition. This extends to our understanding of how inhibition regulates dendritic excitability. Although originally thought of as passive integrators of incoming synaptic inputs, we now know that dendrites express a range of voltage-gated channels and, as a result, can perform a variety of active forms of synaptic integration. This includes the generation of dendritic “spikes”—all-or-none, active

responses initiated in localized dendritic regions or branches following the activation of dendritic voltage-gated sodium and/or Oxymatrine calcium channels, as well as NMDA receptors, which derive their voltage dependence via external magnesium block. These active forms of dendritic integration have been studied in great detail over the last two decades, primarily due to advances that have allowed dendrites of neurons to be investigated directly using either electrophysiological or imaging techniques. What has been missing from the puzzle is an understanding of how this dendritic excitability is regulated by inhibition. In the current issue of Neuron, Müller and colleagues (2012) investigate the role of inhibition in regulating dendritic excitability in hippocampal CA1 pyramidal neurons.

This work was supported by

This work was supported by selleck products a Grant-in-Aid for Scientific Research on Priority Areas from MEXT, Japan (K. Mori and M.Y.), and a Grant-in-Aid for Scientific Research from JSPS (K. Mori and M.Y.). “
“The medial prefrontal cortex (mPFC) has been implicated in the regulation and expression of defensive behaviors in rodents, including learned fear and its extinction (Burgos-Robles et al., 2007) as well as innate anxiety (Deacon et al., 2003, Lacroix et al., 2000, Shah et al., 2004, Shah and Treit, 2003 and Shah and Treit, 2004). Our prior work has suggested that during the expression of innate anxiety,

the mPFC works in concert with a major input source, the ventral hippocampus (vHPC) (Adhikari et al., 2010b). Whether and how neural activity in the mPFC

relates to anxiety-like behavior is unclear. During cognitive tasks, single-unit recordings in the mPFC have task-related firing patterns (Gemmell et al., 2002, Jones and Wilson, 2005, Jung et al., 1998, Pratt and Mizumori, 2001 and Sigurdsson et al., 2010) as well as functional interactions with the hippocampus (Jones and Wilson, 2005, Siapas et al., 2005, Sigurdsson et al., 2010 and Taxidis et al., 2010). However, it is unknown if mPFC activity is modulated by anxiety-related task features. Furthermore, the relationship between task-related firing patterns and functional coupling with the hippocampus is unclear. The elevated plus maze (EPM) is an extensively studied test of innate anxiety selleck chemical in rodents (Hogg, 1996). The EPM is conducted in a plus-shaped maze with four arms, two Dipeptidyl peptidase of which are enclosed by high walls and two of which are left open. Wild-type mice generally make fewer entries into and spend less time exploring the aversive open arms, compared to the relatively safe closed arms. Both the mPFC (Gonzalez et al., 2000 and Shah and Treit, 2004) and vHPC (Bannerman et al., 2002, Bannerman et al., 2004 and Kjelstrup et al., 2002) have been shown to be required for normal anxiety-related behaviors in the EPM. The monosynaptic unidirectional projection from the vHPC to the mPFC (Parent et al., 2010 and Verwer et al.,

1997) suggests the possibility that these two areas may be part of a functional circuit involved in anxiety-related behavior. Consisent with this notion, we recently found that theta-frequency (4–12 Hz) synchrony between the mPFC and the vHPC tracked and predicted anxiety-related behavior in the EPM (Adhikari et al., 2010b). These findings lead to following hypotheses: that mPFC neurons represent the anxiety-related features of the EPM; that this representation arises due to input from the vHPC; and that this representation is used by the animal to guide anxiety-related behavior in the maze. To test these hypotheses, we recorded mPFC single units and vHPC local field potentials from mice during exploration of standard and modified EPMs.

, 2002) A likely mechanism for presynaptic recruitment requiring

, 2002). A likely mechanism for presynaptic recruitment requiring the intracellular region of PTPσ (Figures 4D and 4E) is binding of the second phosphatase domain (D2) to α-liprins (Pulido et al., 1995). α-Liprins directly interact with

CASK, RIMs, and ERC/ELKS/CAST and are important for presynaptic differentiation in Drosophila and Caenorhabditis elegans ( Stryker and Johnson, 2007). The mechanism linking TrkCTK- and TrkCTK+ to glutamatergic postsynaptic proteins is not yet known but presumably occurs via the shared extracellular, transmembrane, and 75-aa membrane-proximal intracellular region. TrkCTK- (NC2) could further recruit the scaffold protein tamalin to activate Arf6-Rac signaling ( Esteban et al., 2006) and TrkCTK+ could recruit and activate PLCγ, Shc, and Frs2 leading to Ras and PI3-kinase ( Huang and Reichardt, 2003). The existence of eight alternatively spliced TrkC variants Y-27632 cost possessing different intracellular regions and a common extracellular region may contribute to diversity of glutamatergic postsynaptic composition. We show here that TrkC is required in cortical neurons in vivo for development of dendritic spines, a function that does not require TrkC kinase activity (Figures 8A–8D). These data indicate a noncatalytic function of TrkC in morphological excitatory synaptogenesis in vivo. Linkage RO4929097 in vivo of NTRK3 to panic

disorder ( Armengol et al., 2002), obsessive-compulsive disorder MTMR9 ( Alonso et al., 2008), and childhood-onset mood disorders ( Feng et al., 2008) in patients supports the importance of TrkC for cognitive function.

Deletion of all TrkC isoforms in mice (NTRK3−/−) results in earlier postnatal lethality by several weeks compared with deletion of only the kinase-active isoforms (NTRK3TK−/−) ( Klein et al., 1994 and Tessarollo et al., 1997). The earlier lethality with additional loss of the noncatalytic isoforms may be in part because of a defect in synaptogenesis. Brain-specific transgenic overexpression of TrkC increases anxiety-related behaviors and markedly increases hippocampal CA1 field EPSPs in vivo after classical conditioning or LTP induction ( Dierssen et al., 2006 and Sahun et al., 2007). Such outcomes are consistent with enhanced glutamatergic synapse development, at the expense of inhibitory GABAergic synapses, upon TrkC overexpression. However, these global genetic manipulations clearly have multiple consequences. The in vivo knockdown of TrkC performed here also did not specifically assess the role of TrkC interaction with PTPσ. A more specific TrkC knockin will be needed to precisely define the role of its interaction with PTPσ in vivo without altering NT-3 and kinase-mediated functions. Consistent with the proposed dual function of PTPσ, Ptprs−/− mice also show multiple defects, including increased lethality, ataxia, and neuroendocrine dysplasia, as well as altered hippocampal and cortical development ( Elchebly et al., 1999, Meathrel et al.

The resulting detoxified whole cell diphtheria–tetanus–pertussis

The resulting detoxified whole cell diphtheria–tetanus–pertussis (DTP) vaccine – DTPlow, – was not only safer, but could be up to fifty times cheaper than that of DTaP. Our research had further showed that removal of LPS allowed for the purification

selleck chemical of MPLA, which is potentially an extremely inexpensive adjuvant. The 2009 A/H1N1 pandemic Modulators called for Butantan to take on an additional temporary role to provide pandemic vaccine to the Ministry of Health by filling a large number of doses imported as bulk product from international producers. Our proposal to vaccinate grammar school children (7–11 years old) to prevent the spread of seasonal influenza from schools to families was therefore curtailed. We did, however, initiate a demonstration trial among 5000 children in the São Paulo area. If results of this ambitious trial, conducted following stringent international practices, corroborate the positive impact of similar strategies [8], it might be recommended to immunize about 1 million children in Brazil. Technology

transfer is complex. It entails a great deal of responsibilities on the part of the technology provider and technical and managerial capability on the part of the recipient. Above all, technology transfer is a joint venture based on mutual trust and commitment. A major objective must also be for the project to be sustainable, which implies incorporation of new developments into the process

and, ultimately, MEK phosphorylation technology independence for the recipient. In the future, Butantan will seek ways to increase its production capacity in order to meet the demand for influenza vaccine, either by improving procedures within the large production plant, or by investigating new technologies. The authors, all investigators of Instituto Butantan, a Govermental Research Institute, have no conflicts of interest. “
“The Serum Institute of India (SII) is the world’s fifth largest producer of vaccines, with an Thymidine kinase installed capacity of over 1 billion doses. SII’s core competence in mass production of cell-culture derived products makes it a major supplier of measles, mumps and rubella, as well as diphtheria, pertussis and tetanus vaccines through the United Nations Children’s Fund. Given this experience and capacity, SII was selected in 2006 to participate in the World Health Organization (WHO) technology transfer initiative to strengthen the capacity of developing countries to produce pandemic influenza vaccine [1]. Countries such as India, with very large populations but no demand for seasonal influenza vaccine, face additional technological and financial challenges in ensuring an adequate supply of influenza vaccine.