#cr3 ep 91

[zeephyre]

CRITICAL ROLE CAMPAIGN 3 EPISODE 91 SPOILERS

Fuck you Sam Riegel, with great love and even greater grief.

“Some connections are made with wire, some are made with love, some are made with wood. But they all matter. And even in this dark cave, they make every day a smiley day.”

I don't feel like talking about....much of anything that happened in this episode. Otohan is gone. Good.

I was....so stressed that entire combat, and at some point, it started feeling like I was... there, watching her get back up every time they knocked her down. It was getting really fucking hopeless and I knew everyone at fhe table was feeling it.

But, God, that moment when matt understood what sam was planning when he described targeting his core. The moment it sunk and shattered his fucking heart is the moment my heart too. The moment Sam started to cry... all of it, every excruciating moment from that point onwards I couldn't stop crying, I don't think I saw the fucking screen for 95% of that.

I cried earlier when Imogen finally got through to her mother. But... I think sometimes I forget how...painful it is for me to lose these characters. The last time I felt this much sorrow and anger and grief, was when Otohan killed Fearne, Orym and Laudna and LYdna couldn't be saved.

We don't know...if we can even save FCG. They're aoerian tech, and that could complicate...everything.

Who will tell Frida that their Faithful Caregiver is gone?

[undead-knick-knack]

When your group is being attacked and the only thing you can do is play dead

[kouichikimura]

SAMUEL BRENT OSCAR RIEGEL

[rhysnolastname]

Also Cr3 ep 91 Sam Riegel when I get you

[phenixfarts]

I just finished watching cr3 91 and went from aaaall that straight into ep 92 and the HOTDOGGGGGG

[studyingbymylonesome]

Extra pyramidal symptoms and D2 antagonism in antipsychotics

Several different pharmacological theories have been proposed to account for the atypicality of SGAs. One proposed mechanism is antagonism of the 5-HT2A receptor, which is thought to “balance” striatal dopamine signaling and thus reduce extrapyramidal side effects (EPS)9,10,11. However, the observation that the SGA amisulpride, which is considerably more D2 selective over 5-HT2A yet still exhibits reduced EPS, suggests that this theory cannot account for all examples of atypicality12, 13.

Another enduring theory of atypicality is based on the dissociation kinetics of APDs from the D2R. This concept originated from the observation that some atypical APDs have lower affinity for the D2R than typical APDs14,15,16, which was later demonstrated to be due to a faster dissociation rate17,18,19. This led Seeman and Kapur to propose the “fast off hypothesis,” whereby rapid dissociation from the D2R contributes to the reduced side effect profile of atypical APDs13. Key to this hypothesis is the rapid and transient nature of synaptic dopamine signaling. Rapid dissociation of an antagonist will allow a greater fraction of D2Rs to be bound by the transiently high local concentrations of released dopamine, therefore out-competing the antagonist in a surmountable fashion. In contrast, an antagonist with a slow dissociation rate is unlikely to dissociate from the D2R in the short time frame between dopamine release and re-uptake, blocking the receptor regardless of the local concentration of dopamine that is achieved, i.e., making the antagonism effectively insurmountable20.The link between dissociation rate and “atypicality” has been questioned, however, based in part on the fact that the atypical APD olanzapine has relatively high affinity for the D2R and should, in theory, dissociate as slowly from the D2R as the typical APD haloperidol3. This inference is based on the widely held assumption that APDs exhibit similar association rates (k on) for the D2R and therefore that affinity is essentially driven by differences in dissociation rate. Although association rates have widely been assumed to be diffusion limited, we recently found that the association rates differ by several orders of magnitude across a range of structurally diverse D2R agonists21, demonstrating that the mechanisms that determine association rate can vary greatly with ligand structure.

The majority of drug-receptor-binding models assume free diffusion of analytes such that the dynamics of the system are reaction-limited. In certain tissue microenvironments, however, this assumption may not be valid, due, in part, to limitations on free diffusion arising from physical barriers. For example, the small aqueous compartment within a dopamine synapse (estimated to be 0.09–0.4 μm3)22 is unlikely to mix well with the bulk aqueous phase surrounding the synapse under the temporal and spatial scales over which neurotransmission operates. This may have important implications with regard to the blockade of dopamine synaptic signals and the ability of APDs to rebind free receptors. Rebinding in this case describes the process whereby a reversibly bound ligand dissociates from a receptor into the local aqueous environment but then rebinds the same or a nearby receptor before it is able to diffuse from the synaptic cleft23, effectively maintaining a higher concentration of the drug near the receptor. Under these conditions, the degree to which an individual drug rebinds is determined by receptor density, the association rate constant, and anatomical and physicochemical factors affecting the diffusion of the ligand away from the receptor24.

Currently available equilibrium and kinetic data on the binding of APDs to the D2R were derived over the past several decades using an assortment of different methods. The most common method has been to use radiolabeled compounds18, 19, 25, although not all APDs are available as radioligands. Alternatively, competition association assays formulated with a single radioligand/tracer can enable the kinetics of unlabeled ligands to be calculated26, 27. We have recently developed such an assay utilizing time-resolved fluorescence resonance energy transfer (TR-FRET) to measure the binding kinetics of unlabeled D2R agonists21, 28. In the present study, we use this method to determine the kinetics of an extensive series of APDs under physiological temperature and sodium ion concentration, and in doing so explore the kinetic basis for on-target side effects. We find that association rates, but not dissociation rates, correlate with EPS. EPS were predicted by a rebinding model that integrates association and dissociation rates within the microenvironment of postsynaptic D2Rs to calculate the net rate of reversal of receptor blockade. In contrast, prolactin elevation was directly correlated with APD off-rate from D2R. Thus, optimizing binding kinetics at the D2R may result in APDs with improved therapeutic profile.

results;

It has been widely assumed that association rates for APDs are diffusion limited and therefore comparable, meaning that the dissociation rate determines their affinity37, 38. Our TR-FRET data, however, revealed a surprisingly wide range of both association and dissociation rates across the ligands studied, demonstrating the importance of directly measuring rate constants. For example, the suggestion that the high-affinity atypical APDs olanzapine and risperidone should have k offvalues similar to haloperidol3 is not supported by our kinetic data.

Consistent with the fast-dissociation hypothesis of APD atypicality, we found that hyperprolactinemia was correlated with the dissociation rate (k off), with ligands that were the slowest to dissociate from the D2R displaying the greatest liability for prolactin elevation in patients. Surprisingly, however, we found it was k on and not k off that was correlated with the incidence of EPS. Thus, drugs that bind more rapidly have greater liability of EPS, challenging the hypothesis that dissociation rate is the sole determinant of a compound’s liability to produce this side effect13. To illustrate, the typical APD chlorpromazine has a k off value similar to that of clozapine, but has much greater EPS liability. The increased propensity for EPS of chlorpromazine relates instead to its rapid association rate (k on). A recent study by Sahlholm and colleagues is consistent with this interpretation. These authors used D2R-evoked potassium channel activation to estimate receptor kinetics39, 40. Interestingly, the off rates determined by this indirect measurement, which were broadly consistent with the values obtained in the current study, did not distinguish between the typical and atypical APDs.

This, combined with the close correlation between rebinding rates and EPS, leads us to speculate that there is a minimum level of stimulation of postsynaptic D2Rs that must be maintained in order to avoid EPS. The ability of dopamine transmission to remain above this threshold in the presence of an APD is determined in large part by the APD’s rebinding rate. It is important, however, to acknowledge that the data presented in this study do not rule out alternative mechanisms that may contribute to the overall side effect profile of APDs, e.g., agonism at 5-HT1A

interestingly, and in contrast to EPS, prolactin elevation was not correlated with k r, reflecting the lack of correlation with k on. This may reflect that dopamine and APDs diffuse into the pituitary through the hypothalamic–pituitary portal system as opposed to a synaptic apposition42,43,44. Since ligands diffuse more freely around D2Rs on pituitary lactotrophs, their behavior conforms to the laws of mass action and rebinding may be negligible. As a consequence, the rate of reversal of APD-receptor occupancy, and thus excess prolactin release, will depend solely on the dissociation rate constant of APDs through the phenomenon of insurmountable antagonism.

To summarize, we propose to expand the kinetic hypothesis for APD side effects by considering not only the dissociation rate (and therefore propensity to display insurmountable antagonism), but also their association rate and potential for receptor rebinding, leading to increased competition with dopamine at the synapse (see Fig. 5a). Based on this scheme, we propose the following three broad classes of compounds to explain how these different kinetic characteristics may influence on-target side effects in different tissues:

1.Fast on, slow off compounds, e.g., haloperidol. The fast on rate results in a high receptor rebinding potential at D2Rs apposed to dopamine release sites in the striatum and therefore high EPS. In contrast, in the pituitary, the slow dissociation rate results in insurmountable antagonism at D2Rs leading to increased prolactin release.

2.Fast on, fast off compounds, e.g., chlorpromazine. Again, the fast on rate leads to high rebinding potential in the striatum and high EPS, but fast off rates result in surmountable antagonism and thus reduced propensity for hyperprolactinaemia.

3.Slow on, fast off compounds, e.g., clozapine. Slow on rates result in lower rebinding potential in the striatum and low EPS, and fast off rates lead to surmountable antagonism and reduced hyperprolactinemia.