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About University of California

The University of California, founded in 1869, is the largest public university in the United States. The University's constituents number more than 244,000 students, over 138,000 faculty and staff, 10 campuses, three national labs, five medical centers, and a collection of agricultural and natural resource centers. The Office of the Chief Investment Officer manages $93 billion in endowment, retirement, and working capital assets on behalf of the University.

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Dopamine projections to the basolateral amygdala drive the encoding of identity-specific reward memories

Feb 23, 2024

Abstract To make adaptive decisions, we build an internal model of the associative relationships in an environment and use it to make predictions and inferences about specific available outcomes. Detailed, identity-specific cue–reward memories are a core feature of such cognitive maps. Here we used fiber photometry, cell-type and pathway-specific optogenetic manipulation, Pavlovian cue–reward conditioning and decision-making tests in male and female rats, to reveal that ventral tegmental area dopamine (VTADA) projections to the basolateral amygdala (BLA) drive the encoding of identity-specific cue–reward memories. Dopamine is released in the BLA during cue–reward pairing; VTADA→BLA activity is necessary and sufficient to link the identifying features of a reward to a predictive cue but does not assign general incentive properties to the cue or mediate reinforcement. These data reveal a dopaminergic pathway for the learning that supports adaptive decision-making and help explain how VTADA neurons achieve their emerging multifaceted role in learning. Access options Get Nature+, our best-value online-access subscription $29.99 / 30 days $209.00 per year Prices vary by article type from$1.95 Additional access options: Fig. 1: Dopamine is released in the BLA during cue–reward learning. Fig. 2: Optical inhibition of VTADA→BLA projections during cue–reward pairing attenuates the encoding of identity-specific cue–reward memories. Fig. 3: Previously learned cue–reward relationships block encoding of new identity-specific cue–reward memories. Fig. 4: Optical stimulation of VTADA→BLA projections during cue–reward pairing unblocks encoding of identity-specific cue–reward memories. Data availability All data that support the findings of this study are available as Supplementary Information . Source data are provided with this paper. Code availability Custom-written MATLAB code is available from the corresponding author upon request. The basic code is available via Dryad ( https://doi.org/10.5068/D1109S ). References Steinberg, E. E. et al. A causal link between prediction errors, dopamine neurons and learning. Nat. Neurosci. 16, 966–973 (2013). Costa, K. M., et al. The role of the orbitofrontal cortex in creating cognitive maps. Nature Neurosci. https://doi.org/10.1038/s41593-022-01216-0 (2022). Lutas, A. et al. State-specific gating of salient cues by midbrain dopaminergic input to basal amygdala. Nat. Neurosci. 22, 1820–1833 (2019). Kamin, L. J. Predictability, surprise, attention, and conditioning. in Punishment Aversive Behavior (eds Church, R. M. & Campbell, B. A.) 279–296 (Appleton-Century-Crofts, 1969). Rescorla, R. A. Learning about qualitatively different outcomes during a blocking procedure. Anim. Learn. Behav. 27, 140–151 (1999). Paxinos, G. & Watson, C. The Rat Brain in Stereotaxic Coordinates (Academic Press, 1998). Collins, A. L. et al. Nucleus accumbens cholinergic interneurons oppose cue-motivated behavior. Biol. Psychiatry 86, 388–396 (2019). Acknowledgements This research was supported by NIH grant DA035443 and MH126285 (to K.M.W. ), NIH grant DA057084 (to K.M.W. and M.J.S. ), NSF GRFP (to A.C.S. ), NSF CAREER 2143910 (to M.J.S. ), the Staglin Center for Behavior and Brain Sciences, and the Wendell Jeffrey and Bernice Wenzel Term Chair in Behavioral Neuroscience (to K.M.W.). Author information Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA Ana C. Sias, Yousif Jafar, Caitlin M. Goodpaster, Kathia Ramírez-Armenta, Tyler M. Wrenn, Nicholas K. Griffin, Keshav Patel, Alexander C. Lamparelli, Melissa J. Sharpe & Kate M. Wassum Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, USA Melissa J. Sharpe & Kate M. Wassum Integrative Center for Learning and Memory, University of California, Los Angeles, Los Angeles, CA, USA Melissa J. Sharpe & Kate M. Wassum Integrative Center for Addictive Disorders, University of California, Los Angeles, Los Angeles, CA, USA Melissa J. Sharpe & Kate M. Wassum Department of Psychology, University of Sydney, Sydney, New South Wales, Australia Melissa J. Sharpe Yousif Jafar Caitlin M. Goodpaster Kathia Ramírez-Armenta Tyler M. Wrenn Nicholas K. Griffin Keshav Patel Alexander C. Lamparelli Melissa J. Sharpe Kate M. Wassum Contributions K.M.W. and A.C.S. designed the research and analyzed and interpreted the data. A.C.S. conducted the research with assistance from Y.J., N.K.G. and A.C.L. C.M.G. and T.M.W. conducted the behavioral blocking experiments. K.R.-A. contributed to the fiber photometry experiments. N.K.G. and K.P. assisted with histological verification. M.J.S. contributed to the design of the blocking experiments and advised on the project and paper. A.C.S. and K.M.W. wrote the paper. Corresponding author Peer review Peer review information Nature Neuroscience thanks Laura Bradfield and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Additional information Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Extended data To characterize the endogenous activity of BLA neurons, we used fiber photometry to record fluorescent activity of the genetically encoded calcium indicator GCaMP6f 67 in the BLA of male and female rats. (a) Top: Representative fluorescent image of GCaMP6f expression and fiber placement in the BLA. Bottom: Fiber photometry approach for bulk calcium imaging in BLA neurons. (b) Schematic representation of GCaMP6f expression and placement of optical fiber tips in BLA for all subjects. (c) Pavlovian long-delay conditioning procedure schematic. CS, 30-s conditioned stimulus (aka, ‘cue’, white noise or click) followed immediately by reward outcome (O, sucrose solution or grain pellet). (d) Food-port entry rate during the cue relative to the preCue baseline period, averaged across the 2 cues for each Pavlovian conditioning session. Across training, rats developed a Pavlovian conditional approach response of entering the food-delivery port during cue presentation. Two-way RM ANOVA training x cue: F(2.44, 17.07) = 7.97, P = 0.002; training: F(3.30, 23.10) = 4.85, P = 0.008; cue: F(1, 7) = 80.33, P < 0.0001. *P < 0.05, **P < 0.01. N = 8, 4 male rats. (e-f) BLA neurons are active during the encoding of cue-reward memories. BLA neurons were robustly activated both at cue onset and offset when the outcome was delivered. Cue onset responses beginning on the first conditioning sessions have been detected previously 2 . These novelty responses rapidly attenuate if the stimuli are not associated with reward 24 . (e) Quantification of maximal (peak) GCaMP6f z-score ∆F/F during the 5-s period following cue onset or outcome delivery compared to the equivalent baseline period immediately prior to cue onset. Two-way RM ANOVA training x event: F(2.52, 17.61) = 3.94, P = 0.03; event: F(1.39, 9.71) = 58.63, P < 0.0001; training F(1.71, 11.97) = 2.30, P = 0.15. (f) GCaMP6f fluorescence changes (z-score ∆F/F) in response to cue presentation (blue) and outcome delivery across days of training. Tick marks represent time of outcome collection for each subject. Data from the last six sessions were averaged across 2-session bins (3/4, 5/6, and 7/8). N = 8, 4 male rats. Data presented as trial-averaged, between-subject mean ± s.e.m. with individual data points. *P < 0.05, **P < 0.01, ***P < 0.001 Bonferroni-corrected post-hoc comparisons. Consistent with prior evidence 24 , BLA neurons are activated by rewards and their predictors. BLA activation is particularly robust when the cues can become linked to the identifying features of the rewards they predict. Although these data likely reflect both somatic and non-somatic calcium activity, they are consistent with prior electrophysiological evidence that BLA neurons respond to reward during learning 68 , 69 , 70 , 71 . (a) GRABDA2h fluorescence changes (z-score) in response to cue presentation (blue) and reward delivery across each of the 8 Pavlovian conditioning sessions. (b) Quantification of BLA GRABDA z-scored signal AUC during the 2-s period following cue onset or reward delivery compared to the equivalent baseline period immediately prior to cue onset. Two-way RM ANOVA event: F(1.85, 11.07) = 4.90, P = 0.03; training: F(2.34, 14.03) = 1.13, P = 0.36; training x event: F(3.45, 20.99) = 0.59, P = 0.65. *P < 0.05, relative to preCue baseline, Bonferroni correction. N = 7, 4 male rats. (c) GRABDA fluorescence changes (z-score) in response to cue presentation and reward delivery across each of the 8 Pavlovian conditioning sessions. (d) Quantification of BLA GRABDA z-scored signal AUC during the 1.5-s period following cue onset, cue offset (trace interval), or reward delivery compared to the equivalent baseline period immediately prior to cue onset. Two-way RM ANOVA event: F(2.06, 14.40) = 13.24, P = 0.0005; training: F(3.62, 25.33) = 2.43, P = 0.08; training x event: F(3.60, 25.17) = 2.60, P = 0.07. *P < 0.05, **P < 0.01, ***P < 0.001, relative to preCue baseline, Bonferroni correction. (GRABDA2h: N = 3, 2 male; GRABDA2m: N = 5, 3 male). The slope of the BLA dopamine reward response across training was significantly negative (β = −0.13, confidence interval −0.25 to −0.007; F(1,62) = 4.49, P = 0.04) and signifantly different (F(1,124) = 13.33, P = 0.0004) from the slope of the BLA dopamine cue-onset response across training, which was significantly positive (β = 0.13, confidence interval 0.06 to 0.20; F(1,62) = 13.53, P = 0.0005). Data presented as trial-averaged, between-subject mean ± s.e.m. with individual data points. *P < 0.05, **P < 0.01, ***P < 0.001 Bonferroni-corrected post-hoc comparisons. (a) GRABDA fluorescence changes (z-score) in response to unpredicted delivery of 1, 2, or 3 food pellets. (b) Quantification of BLA GRABDA z-scored signal AUC during the 20-s period following pellet delivery. Two-way RM ANOVA reward period x magnitude: F(1.92, 11.50) = 12.46, P = 0.001; magnitude: F(1.94, 11.66) = 11.04, P = 0.002; reward: F(1, 6) = 7.86, P = 0.03. GRABDA2h: N = 2, 2 male; GRABDA2m: N = 5, 3 male (c) GRABDA fluorescence changes (z-score) in response to unpredicted puff of air to the face. (d) Quantification of BLA GRABDA z-scored trace AUC during the 5-s period following airpuff delivery relative to 5-s preAirpuff baseline. Two-tailed paired sample t-test t(7) = 5.88, P = 0.0006. GRABDA2h: N = 2, 2 male; GRABDA2m: N = 6, 3 male. Data presented as trial-averaged, between-subject mean ± s.e.m. with individual data points. *P < 0.05, ***P < 0.001 Bonferroni-corrected post-hoc comparisons. There was no effect of optical inhibition of VTADA→BLA projections at reward delivery on collection of the food outcomes. (a) Entries into the food-delivery port during the 30-s periods before and after cue presentation during Pavlovian long-delay conditioning. Rats entered the food-delivery port during the 30-s postcue/reward-delivery period more than the preCue baseline period and similarly between groups. training x period: F(4.94,93.85) = 3.00, P = 0.02; training: F(3.13, 59.48) = 8.51, P < 0.0001; period: F(1,19) = 72.60, P < 0.0001; virus: F(1,19) = 0.47, P = 0.50; training x virus: F(7,133) = 0.65, P = 0.72; virus x period: F(1,19) = 0.87, P = 0.36; training x virus x period: F(7,133) = 0.71, P = 0.66. ArchT, N = 11, 6 male rats; tdTomato, N = 10, 5 male rats. (b) Percent time spent in the food-delivery port during the 10-s preCue baseline and 10-s postCue offset (including trace interval and reward delivery period) periods during Pavlovian trace conditioning. Rats entered the food-delivery port during the 10-s postCue period more than the preCue period and similarly between groups. training x period: F(1.93,19.27) = 9.68, P = 0.001; training: F(2.59, 25.88) = 9.28, P = 0.0004; period: F(1,10) = 138.50, P < 0.0001; virus: F(1,10) = 14.94, P = 0.003; training x virus: F(4, 40) = 1.35, P = 0.27; virus x period: F(1,10) = 1.37, P = 0.27; training x virus x period: F(4, 40) = 0.05, P = 0.996. ArchT, N = 5, 4 male rats; Control, N = 7, 4 male rats (3 WT/cre-dependent ArchT; 4 Th-cre/cre-dependent tdTomato). Data presented as trial-averaged, between-subject mean ± s.e.m. with individual data points. *P < 0.05, **P < 0.01, ***P < 0.001 Bonferroni-corrected post-hoc comparisons. We cre-dependently expressed ArchT bilaterally in VTADA neurons of male and female Th-cre rats and implanted optical fibers bilaterally over BLA. (a) Bottom: Representative fluorescent image of cre-dependent ArchT-tdTomato expression in VTA cell bodies with coexpression of Th in Th-cre rats. Middle: Strategy for bilateral optogenetic inhibition of VTADA axons and terminals in the BLA of Th-cre rats. Top: Representative image of fiber placement in the vicinity of immunofluorescent ArchT-tdTomato-expressing VTADA axons and terminals in the BLA. (b) Schematic representation of cre-dependent ArchT-tdTomato expression in VTA and (c) placement of optical fiber tips in BLA for all subjects. For half of the control group, we expressed cre-dependent tdTomato in the VTA of Th-cre male and female rats. For the other half, wildtype rats were infused with cre-dependent ArchT (which did not express owing to the lack of cre recombinase) into the VTA. Both groups received bilateral optical fibers above the BLA. Thus, we control for light delivery, viral expression, and genotype. There were no significant behavioral differences between each type of control (lowest P: F(1, 6) = 1.61, P = 0.25). (d) Procedure. A, action (left or right lever press); CS, 30-s conditioned stimulus (aka, ‘cue’, white noise or click) followed immediately by reward outcome (O, sucrose solution or grain pellet). (e) Rats first received 11 sessions of instrumental conditioning, without manipulation, in which one of two different lever-press actions each earned one of two distinct food rewards (for example, left press→sucrose/right press→pellets). Lever-press rate averaged across levers and across the final 2 instrumental conditioning sessions. Two-tailed independent sample t-test t(13) = 1.20, P = 0.25. (f) Rats then received Pavlovian conditioning. During each of the 8 Pavlovian conditioning sessions, each of 2 distinct, 30-s, auditory cues was presented 8 times and terminated in the delivery of one of the food rewards (for example, white noiseꟷsucrose/clickꟷpellets). VTADA→BLA projections were optically inhibited (532 nm, 10 mW, 33 s) during the entirety of each cue-reward period. Light turned on at the onset of each cue and off 3 s following reward delivery. Optical inhibition of VTADA→BLA projections through the cue and reward period did not disrupt development of a Pavlovian conditional goal-approach response. Food-port entry rate during the cue relative to the preCue baseline period, averaged across trials and across the 2 cues for each Pavlovian conditioning session. Thin lines represent individual subjects. Three-way RM ANOVA training x cue: F(3.30, 42.87) = 20.69, P < 0.0001; cue: F(1, 13) = 295.60, P < 0.0001; training: F(3.03.,39.42) = 4.13, P = 0.01; virus: F(1,13) = 1.61, P = 0.23; training x virus: F(7,91) = 0.37, P = 0.92; virus x cue: F(1,13) = 3.05, P = 0.10; training x virus x cue: F(7,91) = 2.17, P = 0.04. By the end of training both groups showed similar elevation in food-port approach during the cues. (g-i) We next gave subjects an outcome-specific Pavlovian-to-instrumental transfer (PIT) test, without manipulation. Controls learned the identity-specific cue-reward memories as evidenced by their ability to use the cues to selectively elevate pressing on the lever associated with the same outcome as predicted by the cue. Conversely, the cues were not capable of guiding lever-press choice in the group for which VTADA→BLA projections were inhibited during Pavlovian conditioning. Rather, for these subjects, the cues caused a general increase in pressing across both levers. (g) Lever-press rates during the preCue baseline periods compared to press rates during the cue periods separated for presses on the lever that, in training, delivered the same outcome as predicted by the cue (Same) and pressing on the other available lever (Different). Three-way RM ANOVA virus x lever x cue: F(1, 13) = 7.35, P = 0.02; virus: F(1, 13) = 4.59, P = 0.05; lever: F(1, 13) = 5.76, P = 0.03; cue: F(1, 13) = 58.87, P < 0.0001; virus x lever: F(1, 13) = 1.91, P = 0.19; virus x cue: F(1, 13) = 12.00, P = 0.004; lever x cue : F(1, 13) = 7.56, P = 0.02. *P < 0.05, **P < 0.01, planned comparisons cue same presses v. preCue same presses and cue different presses v. preCue different presses. Inhibition of VTADA→BLA projections during cue-reward learning prevents subjects from learning identity-specific cue-reward memories, but does not prevent the assignment of general incentive properties to the cues that supports non-discriminate cue-induced motivation. (h) Elevation in lever presses on the Same lever [(Same lever presses during cue)/(Same presses during cue + Same presses during preCue)], relative to the elevation in pressing on the Different lever [(Different lever presses during cue)/(Different presses during cue + Different presses during preCue)], averaged across cues during the PIT test. Two-way RM ANOVA virus: F(1, 13) = 2.21, P = 0.16; lever: F(1, 13) = 1.67, P = 0.22; virus x lever: F(1, 13) = 1.14, P = 0.30. (i) As in training, during the PIT test the conditional goal-approach response was similar between groups, further indicating that even longer duration inhibition of VTADA→BLA projections during cue-reward learning does not disrupt development of conditional responses. Food-port entry rate during the cues relative to the preCue baseline periods, averaged across cues during the PIT test. Two-way RM ANOVA cue: F(1, 13) = 44.71, P < 0.0001; virus: F(1, 13) = 0.08, P = 0.79; virus x cue: F(1, 13) = 0.61, P = 0.45. *P < 0.05, **P < 0.01, ***P < 0.001, Bonferroni correction. ArchT, N = 7, 4 male rats; Control N = 8, 4 Th-cre/tdTomato 2 male rats, 4 wildtype cre-dependent ArchT 2 male rats. Data presented as trial-averaged, between-subject mean ± s.e.m. with individual data points. *P < 0.05, **P < 0.01, ***P < 0.001 Bonferroni-corrected post-hoc comparisons. These data confirm that VTADA→BLA projections are needed to link the identifying details of the reward to a predictive cue, but not to reinforce a conditional response or to assign general incentive properties to the cue to support general motivation. There was no effect of optical stimulation of VTADA→BLA projections paired with reward delivery on collection of the food outcomes. Rats entered the food-delivery port during the 30-s postCue/reward-delivery period more than the preCue baseline period and similarly between groups. Three-way RM ANOVA period: F(1, 22) = 46.80, P < 0.0001; training: F(1.50, 32.90) = 3.70, P = 0.047; virus: F(1, 22) = 1.89, P = 0.18; training x virus: F(3, 66) = 1.48, P = 0.23; training x period: F(2.55, 56.04) = 0.22, P = 0.85; virus x period: F(1, 22) = 0.04, P = 0.84; training x virus x period: F(3, 66) = 0.51, P = 0.68. *P < 0.05, **P < 0.01 relative to preCue baseline, Bonferroni correction. ChR2, N = 11, 6 male rats; eYFP, N = 13, 6 male rats. Data presented as trial-averaged, between-subject mean ± s.e.m. with individual data points. *P < 0.05, **P < 0.01, ***P < 0.001 Bonferroni-corrected post-hoc comparisons. To assess the reinforcing properties of VTADA→BLA activation, rats were given 2 sessions of intracranial self-stimulation (ICSS) in a context different from that of prior conditioning. Nose pokes in the active port triggered 1-s blue light delivery (473 nm; 10 mW; 25 ms pulse width; 20 Hz). Data show total active nose pokes compared to inactive nose pokes across 2, 1-hr ICSS sessions. Activation of VTADA→BLA projections was not reinforcing. Rats expressing ChR2 showed similar levels of active nose pokes as the eYFP control group in the first session and this decreased to the level of the inactive nose pokes in the second session. Three-way RM ANOVA session x virus x nose poke: F(1, 22) = 5.00, P = 0.04; virus x nose poke: F(1, 22) = 5.18, P = 0.03; session x virus: F(1,22) = 5.18, P = 0.03; session x nose poke: F(1, 22) = 1.24, P = 0.28; session: F(1, 22) = 3.05, P = 0.09; virus: F(1, 22) = 1.94, P = 0.18; nose poke: F(1, 22) = 54.66, P < 0.0001. Elevated active v. inactive port nose poking in both the eYFP and ChR2 groups could have resulted from the prior association formed between blue light and reward delivery during compound conditioning. If true, then this could have extinguished by the second session in the ChR2 group, potentially indicating that VTADA→BLA projection activity during either initial learning or online during the ICSS session may contribute to the reward expectation and/or learning processes that contribute to extinction. Alternatively, the nose poking in both groups could reflect salience of the light delivery, which could habituate more quickly in the ChR2 group. ChR2, N = 11, 6 male rats; eYFP, N = 13, 6 male rats. Data presented as trial-averaged, between-subject mean ± s.e.m. with individual data points. **P < 0.01, ***P < 0.001 Bonferroni-corrected post-hoc comparisons.

University of California Investments

5 Investments

University of California has made 5 investments. Their latest investment was in Allogene Therapeutics as part of their Convertible Note on September 06, 2018.

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University of California Investments Activity

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9/6/2018

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Allogene Therapeutics

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University of California Portfolio Exits

5 Portfolio Exits

University of California has 5 portfolio exits. Their latest portfolio exit was Allogene Therapeutics on October 11, 2018.

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University of California Fund History

3 Fund Histories

University of California has 3 funds, including UC Investment Fund.

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Fund

Fund Type

Status

Amount

Sources

12/15/2015

UC Investment Fund

$250M

2

Regents Endowment Fund

0

UC Innovation and Entrepreneurship Initiative

10

Closing Date

12/15/2015

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UC Investment Fund

Regents Endowment Fund

UC Innovation and Entrepreneurship Initiative

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Amount

$250M

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0

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University of California Partners & Customers

10 Partners and customers

University of California has 10 strategic partners and customers. University of California recently partnered with UC Davis, and Orgenesis on June 6, 2023.

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Type

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6/7/2023

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United States

Orgenesis Inc. GERMANTOWN, Md. Orgenesis and University of California, Davis Sign Partnership Agreement for Rollout of Cell and Gene Therapy Mobile Processing Units and Labs Throughout California.

`` We believe that this partnership between Orgenesis , UC Davis Health , and the University of California system will become a blueprint for decentralizing the development and manufacturing of CGTs , while demonstrating the benefits of our OMPUL design for the US and international healthcare markets , '' said Vered Caplan , CEO of Orgenesis .

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4/13/2023

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United States

University of California Agreement with Wiley Expands to all 10 UC campuses

By piloting its shared funding model in partnership with publishers of all sizes , including Wiley , UC is demonstrating a sustainable approach to open access for research-focused institutions .

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11/4/2022

Partner

United States

Simplilearn and the University of California, Irvine Division of Continuing Education Partner for a Cybersecurity Boot Camp

Simplilearn , a global digital skills training provider , announced its partnership with the University of California , Irvine Division of Continuing Education for a Cybersecurity boot camp .

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10/1/2022

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France

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9/26/2022

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10/1/2022

9/26/2022

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Partner

Partner

Partner

Partner

Business Partner

Country

United States

United States

United States

France

United States

News Snippet

Orgenesis Inc. GERMANTOWN, Md. Orgenesis and University of California, Davis Sign Partnership Agreement for Rollout of Cell and Gene Therapy Mobile Processing Units and Labs Throughout California.

`` We believe that this partnership between Orgenesis , UC Davis Health , and the University of California system will become a blueprint for decentralizing the development and manufacturing of CGTs , while demonstrating the benefits of our OMPUL design for the US and international healthcare markets , '' said Vered Caplan , CEO of Orgenesis .

University of California Agreement with Wiley Expands to all 10 UC campuses

By piloting its shared funding model in partnership with publishers of all sizes , including Wiley , UC is demonstrating a sustainable approach to open access for research-focused institutions .

Simplilearn and the University of California, Irvine Division of Continuing Education Partner for a Cybersecurity Boot Camp

Simplilearn , a global digital skills training provider , announced its partnership with the University of California , Irvine Division of Continuing Education for a Cybersecurity boot camp .

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University of California Team

5 Team Members

University of California has 5 team members, including current Chief Operating Officer, Arthur Guimaraes.

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Title

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Arthur Guimaraes

Chief Operating Officer

Current

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Arthur Guimaraes

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Work History

Title

Chief Operating Officer

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Status

Current

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