, 2004), and in the thick/pale stripes of macaque V2 (Lu et al., 2010). The direction preference map in V4 showed some common properties as

those found in MT and V2, including similarity in domain size and the orthogonal relationship between preferred BMN 673 datasheet direction and orientation angles (Lu et al., 2010; Kaskan et al., 2010). However, the direction preference maps in V4 also showed features that are distinct from those found in all these other areas. First, V4 direction-preferring domains only appear in restricted regions, rather than in the entire V4 area. Second, many V4 direction-preferring domains appear to be isolated singulars, without any neighboring domains for other directions. Third, these domains overlap not only with orientation-preferring domains but also with color-preferring domains. It is understandable that a direction click here map in the ventral pathway may have a different clustering architecture than its counterparts in the dorsal pathway. A precedent for this principle was found, for example, in motion maps of V2 (Lu et al., 2010), where the direction maps differ in architecture from those found in MT (Malonek et al., 1994; Xu et al., 2004; Kaskan et al., 2010) or cat area 18 (Shmuel and Grinvald, 1996). Thus, this functional architecture may suggest a distinct functional computation in the visual system. Direction-preferring

domains found in previous studies either have been shown in an area not considered to signal color (e.g., MT; Malonek et al., 1994; Xu et al., 2004; Kaskan et al., 2010) or avoid color-preferring regions (e.g., in thick/pale stripes of V2; Lu et al., 2010). others Our data show that, in V4, about one fourth of direction-preferring pixels overlap with color-preferring pixels, suggests that these direction-selective neurons may be involved in detection of color motion. Another possibility is that motion cues in V4 are used for surface definition and thus are processed by surface-processing neurons, which were revealed by color versus luminance imaging (e.g., Figure 1D). These results,

however, differ from the findings in a recent fMRI-guided recording study in which color cells recorded from globs rarely showed direction selectivity (Conway et al., 2007). We noted that the V4 color glob neurons they recorded from were mostly from anterior wall of the lunate sulcus, while our imaging and recordings were all from dorsal part of the lunate gyrus. Therefore, it is possible that different parts of V4 may have different color-direction interactions. The separation of motion and color/form information in the primate visual system has been considered to be strong support for the concept of parallel processing of visual information. In particular, areas MT and V4 are often referred to as motion and color/form centers, respectively (Zeki et al., 1991).

, 2006), and endothelial cells ( Daneman et al., 2010) also did not exhibit any in situ signal in neuronal dendrites ( Figures S7E–S7I). Analysis of the different mRNA distribution patterns

indicates that the dendrite to soma ratio for distinct mRNAs is not a constant value and is not solely dependent on the apparent somatic concentration of an mRNA (see Figure 6B). In addition, Dabrafenib ic50 we quantified the ratio of the Dlg4 mRNA between the dendrites and the cell body in single neurons and found a dendrite: soma ratio of ∼30:70 ( Figure S5). The above experiments validate the presence of mRNAs we identified via deep sequencing in the dendrites of cultured hippocampal neurons. To examine the localization of a subset of mRNAs in a more realistic context, we adapted the high resolution in situ hybridization technique for use in rat hippocampal slices and combined it Selleckchem Panobinostat with immunohistochemical labeling of dendrites using an antibody to MAP2 (Figure 7A). We focused our analysis on area CA1, the region from which we microdissected

tissue for deep sequencing and the site of several forms of plasticity that require local translation. We examined the localization of 19 (Dlg4, Map1a, Cacng2, Shank3, Psd, Shank1, Cacna1i, Hpcal4, Nlgn3, Kcnd2, Camk4, Gria2, Cyfip2, Grin2a, Grik2, Kif5a, Kcna2, Actb, and Pclo; 11 are shown in Figure 7) different transcripts and found positive evidence for their presence within the synaptic neuropil ( Figures

7A and 7B). In some fortuitous cases, the MAP2-labeled dendrites were sufficiently well-resolved to allow us to visualize labeled mRNAs associated with dendrites ( Figure 7A). Taken together, these data indicate that the mRNAs identified by deep sequencing can be observed by high-resolution imaging to reside in the synaptic neuropil of hippocampal area CA1. The proteome of an individual synapse is the physical entity that determines the response of either a given synapse to an input, and it is clear that, like other proteomes (e.g., Ingolia et al., 2009), the synaptic proteome is subject to ongoing and dynamic modification by regulated protein synthesis and degradation. The prior identification of mRNAs resident in dendrites and axons have yielded a largely heterogeneous mix of a small number (100 or so) transcripts that did not suggest an ongoing role for local protein synthesis in synaptic function, but rather suggested that local synthesis might be used in special cases during some forms of synaptic plasticity. Here, using next generation sequencing of hippocampal neuropil RNA samples we reveal a surprisingly large number of previously undetected neuropil mRNAs, suggesting that mRNA localization may be more of a rule, than the exception. In addition, many of the proteins that populate the synapse may originate from a local source. Based on current reference databases (NCBI, Rattus norvegicus transcriptome version rn4.

Of these metabolites, propionate and butyrate readily cross the gut-blood and blood–brain barriers via a monocarboxylate transporter ( Karuri et al., 1993,

Bergersen et al., 2002 and Conn et al., 1983). In the brain, propionate and other SCFAs impact neuronal metabolism as well as the synthesis and release of neurotransmitters during early buy CP-690550 neurodevelopment ( Peinado et al., 1993 and Rafiki et al., 2003). Importantly, a careful balance of brain SCFAs must be achieved, as excessive levels have been associated with neural mitochondrial dysfunction and severe behavioral deficits in rodents ( Macfabe, 2012, de Theije et al., 2014a, de Theije et al., 2014b and de Theije et al., 2011). In addition to their direct role in fermentation, commensal gut microbiota express many enzymes with immunomodulatory and neuromodoulatory implications. For example, the gene encoding histidine decarboxylase (HDC), which catalyzes the conversion

of l-histidine to histamine, was recently identified in Lactobacillus FK228 research buy reuteri, a beneficial microbe found in the gut of rodents and humans ( Thomas et al., 2012). Critically, circulating histidine availability is also directly proportional to histidine content and histamine synthesis in the brain ( Schwartz et al., 1972 and Taylor and Snyder, 1971). Histaminergic fibers originate from the tuberomamillary region of the posterior hypothalamus and project widely to most regions of the developing brain, including the hippocampus, dorsal raphe, cerebellum, and neighboring nuclei of the hypothalamus ( Panula et al., 1989). The nearly ability of microbiota to modulate synthesis of a vast array of neuromodulatory

molecules highlight the need for additional studies characterizing of the role of microbiota-derived metabolites on broad neurodevelopmental events. Accumulating evidence draws associations between microbe-generated metabolites during early development and endophenotypes of neuropsychiatric disease. Studies in GF mice revealed that microbial exposure during early life modulated dopamine signaling, neuronal mitochondrial function, neuroplasticity, and motivational behaviors in adult animals (Diaz Heijtz et al., 2011 and Matsumoto et al., 2013). Further, in a mouse model of maternal immune activation during pregnancy, decreased abundance of the beneficial Bacteroides fragilis and increased serum levels of microbe-derived metabolites 4-ethylphenylsulfate and indolepyruvate were observed in exposed offspring. Direct administration of these metabolites to unexposed offspring increased adult anxiety-like behaviors similar to those observed following maternal immune activation, supporting that microbe-generated metabolites may affect brain programming ( Hsiao et al., 2013).

05). Most notably, firing just after the “go” signal (tone offset) was not different on short- and long-latency trials (Figure 6D, third column), in marked contrast to the strong unidirectional relationship between movement initiation latency and postcue firing in the DS task (Figures 3, 4, and 5). There was significantly greater firing in trials with fast compared to slow movement speeds (latency between nose poke exit and reward receptacle

entry), but only within the epoch that followed cue offset (Figure 6E). Thus, the weakly excited neurons in the CD task did not encode movement initiation latency but did encode response speed. To confirm this result and to assess latency and speed encoding in other neurons, we repeated the same analyses shown in Figure 6 on four different nonexclusive groups of neurons: all neurons not analyzed in Figure 6 (nonexcited neurons), the 25% of neurons with the largest firing rate decrease selleck screening library selleckchem in each epoch (inhibited neurons, n = 38), the 25% of neurons with the largest firing rate increase in each epoch (without regard to significance, n = 38), and all 155 neurons pooled together. There was no difference in firing between short- and long-latency trials, or between fast and slow movement speed trials,

at any epoch in any of these groups of neurons (Wilcoxon p > 0.08; not shown). Finally, we asked whether NAc neurons encoded the direction of the upcoming response—contraversive or ipsiversive—and found on average no significant encoding among the excited cells in the four epochs (Wilcoxon p ≥ 0.1). This result is consistent with the previously published findings in this data set, which show ∼6% of neurons significantly encode upcoming response direction, but with no overall bias for contraversive or ipsiversive movement (Taha et al., 2007). In summary, the encoding of approach vigor was much weaker, and occurred in fewer neurons in the inflexible approach CD task than in the flexible approach DS task. In the DS task, the DS-evoked firing was greater nearly when the animal was closer to the operant lever at cue onset (Figures 3, 4, and 5). This apparent proximity signal is intriguing given prior observations

that NAc neurons encode spatial location through “place field”-like activity (e.g., Lavoie and Mizumori, 1994). While it was not possible to assess place-field-like properties of DS-evoked firing because of its brief duration, we were able to assess place-field-like activity of spontaneous firing recorded in the absence of cues during the ITI. Of 126 NAc neurons, 31 exhibited place-field-like activity during the ITI, which we defined as having four or more adjacent points (2 × 2 cm squares) where the firing rate was greater than twice the mean (Figure S6). Consistent with previous findings in the NAc (German and Fields, 2007; Tabuchi et al., 2000; van der Meer and Redish, 2009), the preferred locations were biased toward task-relevant locations (near the reward receptacle and levers).

Because Tai Ji Quan is often practiced in groups in public places such as community centers, parks, and plazas, it offers a unique opportunity for the exchange of ideas, social networking, and developing social and personal relationships among practitioners. Its increasing popularity internationally has made Tai Ji Quan a

resource for promoting cultural exchange and appreciation. this website Like Wushu, Tai Ji Quan serves multiple functions, from the traditional practice of self-defense to its contemporary uses for promoting public health, enhancing quality of life, and facilitating cultural exchange. The multidimensional nature of Tai Ji Quan makes it well suited for people from all walks of life. Static-stance practice is a fundamental skill for practitioners of Tai Ji Quan. The most common types of static-stance practice are Wuji pylon stance (the preparatory form or opening stance

of Tai Ji Quan), Chuan-character pylon stance, and the palm pylon stance. Practicing the static stances not only builds the strength of the legs and hips but also helps establish a sound posture and foundation for learning and practicing more complicated Regorafenib mouse forms/movements. The single-form practice is the most basic way of learning and practicing Tai Ji Quan. For example, Cloud Hand uses the waist as a pivot and drives the arms for coordination, exercising the torso and shoulder joints. The single-form practice can also be used to alleviate pain and fatigue in specific parts of the body. Thus, for individuals who work at a sedentary job, the single-form practice may be a good method for reducing fatigue. Combination

practice refers to practice of movements contained within a form. Repetitive practice of the movements (ward-off, rollback, press, push) involved in the form “Grasp the Peacock’s Tail” exemplifies this. Combination practice plays an important role in mastering correct actions as well as developing basic skills for engaging in more complicated routines (described below). In addition, this practice expands the number muscles and joints involved, thereby extending the benefits of improving flexibility, reducing fatigue, and enhancing fitness. Routine practice represents many a mainstream training method that involves practicing Tai Ji Quan in accordance with its original sequence (e.g., 24 forms). This typically begins with a particular starting form and finishes with a predefined ending form. The push-hand practice is a barehanded training routine performed between two practitioners. Practice of push-hand can be divided into several forms, including fixed-step push-hand, single-hand push, double-hand push, and moving-step push-hand, which requires coordination of the upper and lower limbs. The basics of the push-hand practice are developed through eight techniques, including warding off, rolling back, pressing, pushing, plucking (or grasping), splitting, elbowing, and leaning.

Hazzard for figure assistance.

J.A. was supported by National Eye Institute (NEI)/National Institutes of Health (NIH) grants R01EY018350, R01EY018836, R01EY020672, R01EY022238, R21EY019778, RC1EY020442, Doris Duke selleckchem Distinguished Clinical Scientist Award, Burroughs Wellcome Fund Clinical Scientist Award in Translational Research, Dr. E. Vernon Smith and Eloise C. Smith Macular Degeneration Endowed Chair, and B.J.F. was supported by by NIH T32HL091812 and UL1RR033173. J.A. is named as an inventor on patent applications about age-related macular degeneration filed by the University of Kentucky and is a founder of iVeena Pharmaceuticals, which is commercializing these technologies. “
“Huntington’s disease (HD) is one of the most common dominantly inherited neurodegenerative disorders clinically characterized by a triad of movement disorder, cognitive dysfunction, and psychiatric impairment (Bates et al., 2002). HD neuropathology is characterized by selective and massive degeneration of the striatal medium spiny neurons (MSNs) and, to a lesser extent, the deep layer cortical pyramidal neurons (Vonsattel and DiFiglia, 1998). The disease is caused by a CAG repeat expansion resulting in an elongated polyglutamine (polyQ) stretch near the N terminus of Huntingtin (Htt) (The Huntington’s

Disease Collaborative Research Group, 1993). HD is one of nine polyQ disorders with shared molecular genetic features, such as an inverse relationship between the expanded repeat length and the age of disease onset, and evidence for toxic gain-of-function as a result of Selleck Rucaparib the polyQ expansion (Orr and Zoghbi, 2007). However, each of the polyQ disorders appears to target a distinct subset of neurons

in the brain Megestrol Acetate leading to disease-specific symptoms. Hence, it is postulated that molecular determinants beyond the polyQ repeat itself may be critical to disease pathogenesis (Orr and Zoghbi, 2007). Protein-interacting cis-domains ( Lim et al., 2008) and posttranslational modifications (PTMs) of polyQ proteins ( Emamian et al., 2003 and Gu et al., 2009) can significantly modify disease pathogenesis in vivo. Thus, studying the proteins that interact with domains beyond the polyQ region may provide important clues to disease mechanisms. In the case of HD, several hundred putative Htt interactors have been discovered using ex vivo methods, such as yeast two-hybrid (Y2H) or in vitro affinity pull-down assays, utilizing only small N-terminal fragments of Htt ( Goehler et al., 2004 and Kaltenbach et al., 2007). Such studies have provided insight into Htt’s normal function as a scaffolding protein involved in vesicular and axonal transport and nuclear transcription ( Caviston and Holzbaur, 2009 and Li and Li, 2006). The caveats of the prior Htt interactome studies include the exclusive use of small Htt N-terminal fragments as baits and the isolation of interactors ex vivo.

In order to average across cells, each of which had slightly different Vrest and input resistance (Rin), Transferase inhibitor we replotted the data as a function of Vm during the prepulse (Figure 1C). The number of spikes evoked by the test pulse peaked when the prepulse was near the average Vrest and was suppressed

by prepulses that evoked hyperpolarizations and depolarizations within the physiological range (−10 mV to +20 mV relative to Vrest) (Figure 1D). To test the physiological relevance of the prepulses in the above current-injection experiment, we substituted the test pulse with a visual stimulus: a spot (0.4 mm diameter) that decreased contrast by 100% (i.e., the mean luminance switched to black). check details The number of spikes evoked by the contrast stimulus peaked when the prepulse was near Vrest and was suppressed by prepulses that evoked hyperpolarizations or

depolarizations (Figures 1E, 1G, and 1H). Thus, prepulses evoked by current injection at the soma suppress subsequent visually-evoked, synaptically-driven responses originating at the dendrites. We tested whether the prepulse and associated change in Vm and firing rate could have fed back through the circuitry (i.e., through gap junctions with inhibitory amacrine cells) to suppress the visual response. We injected either hyperpolarizing or depolarizing prepulses in current clamp, as above, and then switched to voltage clamp to record contrast-evoked synaptic currents (Vhold near Vrest, ∼−65 mV). Under these conditions, the prepulses had essentially no effect on the synaptic input (Figure 1F), suggesting that the effect of prepulses on the firing response to contrast depends on intrinsic properties of the ganglion cell and does not involve feedback onto presynaptic neurons. Depolarization and hyperpolarization typically stimulate different sets of voltage-gated channels,

and so it seemed likely Adenosine that the suppressive effects observed by depolarizing and hyperpolarizing prepulses depended on separate mechanisms. Indeed, the time course of suppression differed after the two classes of prepulse. In most experiments below, prepulse current injections were designed to change Vm within the physiological range: +400 pA versus −280 pA, which typically evoked +15 mV versus −10 mV changes in Vm. A depolarizing prepulse suppressed firing to the test pulse across the entire test-pulse duration, whereas a hyperpolarizing prepulse suppressed only the late firing to the test pulse (Figure 2A). The time course of the suppressive effects can be visualized in cumulative firing-rate plots for each stimulus (Figure 2A, inset). We performed a similar analysis in the case where visual contrast replaced the test pulse. In this case, the depolarizing prepulse suppressed firing to contrast across the duration of the response, whereas a hyperpolarizing prepulse suppressed primarily the late firing (Figure 2B).

In addition, hourly health observations were conducted for 4 h following treatment with afoxolaner on Day 0. For both studies, seven days prior to treatment (designated as to Day 0) dogs were infested with 50 adult ticks of approximately equivalent sex ratio, which were removed and counted 48 h later. The dogs were ranked in order of these pre-treatment

tick counts (highest to lowest). The first two dogs were assigned to Block 1, the next click here two dogs to Block 2 and so on until 10 blocks of two dogs each were formed. Within blocks, dogs were randomly assigned to one of two treatment groups. Dogs in Group 1 were untreated controls. Dogs in Group 2 were treated once orally with the appropriate combination of soft chewables containing afoxolaner. Two sizes of chews were used: 0.5 g and 1.25 g, containing 11.3 mg and 28.3 mg of afoxolaner, respectively. The soft chewables are not designed to be divided, therefore, the dosing was administered as closely as possible to the minimum effective dose of 2.5 mg/kg using whole chews. The doses administered to dogs ranged from 2.57 to 3.96 mg/kg body weight in Study 1 and from 2.97 to 3.70 mg/kg body weight in Ribociclib manufacturer Study 2. The dogs

were observed during the 4 h following their treatment and daily throughout the study. Dogs were infested with 50 adult ticks (25 females and 25 males) on the day prior to treatment (Day – 1) and on Days 7, 14, 21, and 28. Forty-eight hours after treatment and 48 h after each of the subsequent re-infestations, ticks were removed and live ticks

were counted. These counts were conducted using a procedure involving Thymidine kinase methodical examination of all body areas using finger tips and/or a coarse tooth comb to sort through the hair and locate all ticks following WAAVP guidelines (Marchiondo et al., 2013). The two studies used unfed adult D. variabilis ticks from two separate laboratory-maintained populations. Each laboratory population had been established from ticks collected in the USA. Personnel responsible for collection of animal health and efficacy data were blinded to the treatment groups. Total counts of live ticks were transformed to the natural logarithm of (count + 1) for calculation of geometric means by treatment group at each time point. Percent reduction from the control group mean was calculated for the treated group at each post-treatment time point using the formula [(C − T)/C] × 100, where C is the geometric mean for the control group and T is the geometric mean for the treated group. The log counts of the treated group were compared to the log counts of the untreated control group using an F-test adjusted for the allocation blocks used to randomize the animals to the treatment groups. The comparisons were performed using a two-sided test with a 5% significance level.

A classic example is navigation through mazes (Tolman, 1938, Hull, 1932 and Olton and Samuelson, 1976). Recordings from the rodent hippocampus and entorhinal cortex have led to important discoveries about the neural encoding of navigation and the representation of space (McNaughton et al., 2006 and Moser et al., 2008). Navigation is composed of a sequence of individual orienting motions, but in contrast to rodent studies of spatial navigation, the neural control of individual orienting motions has been studied most thoroughly in primates, specifically with regard to the control of gaze by the frontal and supplementary eye fields (FEF and SEF) (Schall and

Thompson, 1999 and Schiller and Tehovnik, 2005). As a result of being separated by both different model species and by different behavioral paradigms, literature for the navigation system and literature Luminespib cost for the orienting systems have remained far apart, making few references OSI-744 solubility dmso to each other (but see Arbib, 1997, Corwin and Reep, 1998 and Kargo et al., 2007). Yet the two systems must necessarily interact (Whitlock et al., 2008). As part of bridging the gap between these two fields of research, we took a classic primate behavioral paradigm, memory-guided orienting (Gage et al., 2010 and Funahashi et al., 1991), which is known to be FEF-dependent

(Bruce and Goldberg, 1985 and Bruce et al., 1985), and adapted it to rats. Then, in rats performing the task, we studied a rat cortical area that has long been suggested as homologous to the primate FEF. The area we studied appears in the literature under a large variety of names. These include M2 (Paxinos and Watson, 2004), anteromedial cortex (Sinnamon and Galer, 1984), dorsomedial prefrontal cortex (Cowey and Bozek, 1974), medial precentral cortex (Leichnetz et al., 1987), Fr2 (Zilles, 1985), medial agranular cortex (Donoghue and Wise, 1982 and Neafsey et al., 1986), primary whisker motor cortex (Brecht et al., 2004), and rat frontal eye fields (Neafsey

et al., 1986 and Guandalini, 1998). A theme common to many studies of this area, and shared with the primate FEF, is a role in guiding orienting movements. We targeted a particular point PDK4 at the center of the areas investigated in the studies cited above (+2 AP, ±1.3 ML mm from Bregma), and refer to the cortex around this point as the frontal orienting field (FOF). The homology between rat FOF and primate FEF was first proposed four decades ago by C.M. Leonard (1969), based on the anatomical finding that the FOF, like the FEF, receives projections from the mediodorsal nucleus of the thalamus (Reep et al., 1984), and projects to the superior colliculus (SC) (Reep et al., 1987). Later, Stuesse and Newman (1990) found that the rat FOF also projects to other oculomotor centers in the rat’s brainstem, in a pattern that mimics the oculomotor brainstem projections of the primate FEF.

Although GRIP1b is palmitoylated in heterologous find more cells, endogenous GRIP1 palmitoylation is not well characterized in neurons. Using [3H]palmitate labeling, we first

confirmed that GRIP1 is indeed palmitoylated in primary neurons (Figure 2E). Immunoblotting of ABE samples with a “pan-GRIP1” antibody also showed a robust signal, confirming GRIP1 palmitoylation in both cultured neurons and in intact brain (Figure 2E). To specifically detect GRIP1b palmitoylation, we probed the same ABE samples with our GRIP1b antibody. Strikingly, this suggested that a higher percentage of GRIP1b is palmitoylated in neurons than the well-known palmitoyl-protein PSD-95 (Figure 3A). Their similar subcellular localization suggests that DHHC5 is appropriately positioned to palmitoylate GRIP1b in neurons. Indeed, although GRIP1b protein was detected as early as 5 days in vitro [DIV] (Figure 2F), GRIP1b palmitoylation was detected only at later times (12–19 DIV), coincident with the appearance of DHHC5 (Figure 2F). Moreover,

neurons infected with lentivirus encoding a small hairpin RNA (shRNA) that specifically targets DHHC5 (Figure S2I) showed markedly Afatinib reduced levels of palmitoylated, but not total, GRIP1 (Figures 2G and 2H). Importantly, as a control for potential off-target effects of shRNA, both DHHC5 levels and GRIP1 palmitoylation were rescued by coexpression of shRNA-resistant DHHC5 (Figures 2G and 2H). DHHC5 knockdown and rescue did not affect either palmitoylated or total levels of the known palmitoyl proteins Fyn (Figure 2G) or SNAP25 (data not shown). DHHC5 knockdown did not completely eliminate GRIP1b palmitoylation, suggesting that other PATs, in particular DHHC8, might compensate for loss of DHHC5. Indeed, while infection of a DHHC8-specific (Figures S2J and S2K) shRNA only slightly reduced GRIP1 palmitoylation, coinfection with shRNAs targeting DHHC5 and DHHC8 together reduced GRIP1 palmitoylation to almost undetectable levels (Figures 2G and 2H). Levels of total and palmitoylated SNAP25 and Fyn were unaffected, even in DHHC5 plus DHHC8 knockdown neurons. These results strongly suggest that both

DHHC5 and DHHC8 can palmitoylate GRIP1 in neurons but that DHHC5 is the major endogenous regulator of GRIP1 palmitoylation. Indeed, an antibody that recognizes both DHHC5 and DHHC8 equally SB-3CT revealed that DHHC5 is by far the major of these two PATs in our neuronal cultures (Figure S2L). Thus, in subsequent experiments we focused our attention on DHHC5. Although palmitoylation is reversible, rates of palmitate turnover on neuronal proteins vary widely (Huang and El-Husseini, 2005 and Kang et al., 2008). Palmitate turnover rate can provide insight into the possible function of palmitoylation; rapid turnover suggests a role in dynamic events such as regulated protein trafficking, while slow palmitate turnover suggests a role in long-term static protein targeting.