Bias Profiles Research Articles

Pharmacological interventions for pruritus in adult palliative care patients.

Pharmacological interventions for pruritus in adult palliative care patients.

Biased receptor signalling and intracellular trafficking profiles of structurally distinct formylpeptide receptor 2 agonists.

There is increasing interest in developing FPR2 agonists (compound 43, ACT-389949 and BMS-986235) as potential pro-resolving therapeutics, with ACT-389949 and BMS-986235 having entered phase I clinical development. FPR2 activation leads to diverse downstream outputs. ACT-389949 was observed to cause rapid tachyphylaxis, while BMS-986235 and compound 43 induced cardioprotective effects in preclinical models. We aim to characterise the differences in ligand-receptor engagement and downstream signalling and trafficking bias profile. Concentration-response curves to G protein dissociation, β-arrestin recruitment, receptor trafficking and second messenger signalling were generated using FPR2 ligands (BMS-986235, ACT-389949, compound 43 and WKYMVm), in HEK293A cells. Log(τ/KA) was obtained from the operational model for bias analysis using WKYMVm as a reference ligand. Docking of FPR2 ligands into the active FPR2 cryoEM structure (PDBID: 7T6S) was performed using ICM pro software. Bias analysis revealed that WKYMVm and ACT-389949 shared a very similar bias profile. In comparison, BMS-986235 and compound 43 displayed approximately 5- to 50-fold bias away from β-arrestin recruitment and trafficking pathways, while being 35- to 60-fold biased towards cAMP inhibition and pERK1/2. Molecular docking predicted key amino acid interactions at the FPR2 shared between WKYMVm and ACT-389949, but not with BMS-986235 and compound 43. In vitro characterisation demonstrated that WKYMVm and ACT-389949 differ from BMS-986235 and compound 43 in their signalling and protein coupling profile. This observation may be explained by differences in the ligand-receptor interactions. In vitro characterisation provided significant insights into identifying the desired bias profile for FPR2-based pharmacotherapy.

Linkers in Bitopic Agonists Shape Bias Profile among Transducers for the Dopamine D2 and D3 Receptors.

Bitopic ligands bind both orthosteric and allosteric or secondary binding sites within the same receptor, often resulting in an improvement of receptor selectivity, potency, and efficacy. In particular, for both agonists and antagonists of the dopamine D2 and D3 receptors (D2R and D3R), the primary therapeutic targets for several neurological and neuropsychiatric disorders, bitopic ligand design has proved advantageous in achieving better pharmacological profiles in vitro. Although the two pharmacophores within a bitopic ligand are typically considered the main drivers of conformational change for a receptor, the role of the linker that connects the two has not yet been systematically studied for its relevance in receptor activity profiles. Here, we present a comprehensive analysis of sumanirole and PF592,379-based indole-containing bitopic compounds in agonist activity at D2R and D3R, with a focus on linker chemical space and stereochemistry through testing six distinct chirally resolved linkers and a simple aliphatic linker. The structure activity relationships (SARs) of these linkers are examined extensively, beyond the conventional level, by characterizing the activation of all putative transducers over a 44 min time course. Our multiparametric analysis reveals previously unappreciated specific linker-dependent effects on primary pharmacophores, receptors, transducer activation kinetics, and bias, highlighting the utility of this comprehensive approach and the significance of the linker type in shaping transducer bias profiles.

Optimizing spatio-temporal correlation structures for modeling food security in Africa: a simulation-based investigation

This study investigates the impact of spatio- temporal correlation using four spatio-temporal models: Spatio-Temporal Poisson Linear Trend Model (SPLTM), Poisson Temporal Model (TMS), Spatio-Temporal Poisson Anova Model (SPAM), and Spatio-Temporal Poisson Separable Model (STSM) concerning food security and nutrition in Africa. Evaluating model goodness of fit using the Watanabe Akaike Information Criterion (WAIC) and assessing bias through root mean square error and mean absolute error values revealed a consistent monotonic pattern. SPLTM consistently demonstrates a propensity for overestimating food security, while TMS exhibits a diverse bias profile, shifting between overestimation and underestimation based on varying correlation settings. SPAM emerges as a beacon of reliability, showcasing minimal bias and WAIC across diverse scenarios, while STSM consistently underestimates food security, particularly in regions marked by low to moderate spatio-temporal correlation. SPAM consistently outperforms other models, making it a top choice for modeling food security and nutrition dynamics in Africa. This research highlights the impact of spatial and temporal correlations on food security and nutrition patterns and provides guidance for model selection and refinement. Researchers are encouraged to meticulously evaluate the biases and goodness of fit characteristics of models, ensuring their alignment with the specific attributes of their data and research goals. This knowledge empowers researchers to select models that offer reliability and consistency, enhancing the applicability of their findings.

A logic-incorporated gene regulatory network deciphers principles in cell fate decisions.

Organisms utilize gene regulatory networks (GRN) to make fate decisions, but the regulatory mechanisms of transcription factors (TF) in GRNs are exceedingly intricate. A longstanding question in this field is how these tangled interactions synergistically contribute to decision-making procedures. To comprehensively understand the role of regulatory logic in cell fate decisions, we constructed a logic-incorporated GRN model and examined its behavior under two distinct driving forces (noise-driven and signal-driven). Under the noise-driven mode, we distilled the relationship among fate bias, regulatory logic, and noise profile. Under the signal-driven mode, we bridged regulatory logic and progression-accuracy trade-off, and uncovered distinctive trajectories of reprogramming influenced by logic motifs. In differentiation, we characterized a special logic-dependent priming stage by the solution landscape. Finally, we applied our findings to decipher three biological instances: hematopoiesis, embryogenesis, and trans-differentiation. Orthogonal to the classical analysis of expression profile, we harnessed noise patterns to construct the GRN corresponding to fate transition. Our work presents a generalizable framework for top-down fate-decision studies and a practical approach to the taxonomy of cell fate decisions.

A logic-incorporated gene regulatory network deciphers principles in cell fate decisions

Organisms utilize gene regulatory networks (GRN) to make fate decisions, but the regulatory mechanisms of transcription factors (TF) in GRNs are exceedingly intricate. A longstanding question in this field is how these tangled interactions synergistically contribute to decision-making procedures. To comprehensively understand the role of regulatory logic in cell fate decisions, we constructed a logic-incorporated GRN model and examined its behavior under two distinct driving forces (noise-driven and signal-driven). Under the noise-driven mode, we distilled the relationship among fate bias, regulatory logic, and noise profile. Under the signal-driven mode, we bridged regulatory logic and progression-accuracy trade-off, and uncovered distinctive trajectories of reprogramming influenced by logic motifs. In differentiation, we characterized a special logic-dependent priming stage by the solution landscape. Finally, we applied our findings to decipher three biological instances: hematopoiesis, embryogenesis, and trans-differentiation. Orthogonal to the classical analysis of expression profile, we harnessed noise patterns to construct the GRN corresponding to fate transition. Our work presents a generalizable framework for top-down fate-decision studies and a practical approach to the taxonomy of cell fate decisions.

Ligand bias and inverse agonism on 5-HT2A receptor-mediated modulation of G protein activity in post-mortem human brain.

Whereas biased agonism on the 5-HT2A receptor has been ascribed to hallucinogenic properties of psychedelics, no information about biased inverse agonism on this receptor is available. In schizophrenia, increased 5-HT2A receptor constitutive activity has been suggested, highlighting the therapeutic relevance of inverse agonism. This study characterized the modulation of G protein activity promoted by different drugs, commonly considered as 5-HT2A receptor antagonists, in post-mortem human brain cortex. Modulation of [35S]GTPγS binding to different subtypes of Gα proteins exerted by different 5-HT2A receptor drugs was determined by scintillation proximity assays in brain from human, WT and 5-HT2A receptor KO mice. MDL-11,939 was the only drug having no effect on the basal activity of 5-HT2A receptor. Altanserin and pimavanserin decreased basal activation of Gi1, but not Gq/11 proteins. This effect was blocked by MDL-11,939 and absent in 5-HT2A receptor KO mice. Volinanserin showed 5-HT2A receptor-mediated inverse agonism both on Gi1 and Gq/11 proteins. Ketanserin exhibited 5-HT2A receptor partial agonism exclusively on Gq/11 proteins. On the other hand, eplivanserin and nelotanserin displayed inverse agonism on Gq/11 and/or Gi1 proteins, which was insensitive to MDL-11,939 and was present in KO mice suggesting a role for another receptor. The results reveal the existence of constitutively active 5-HT2A receptors in human pre-frontal cortex and demonstrate different pharmacological profiles of various 5-HT2A receptor drugs previously considered antagonists. These findings indicate that altanserin and pimavanserin possess biased inverse agonist profile towards 5-HT2A receptor activation of Gi1 proteins.

Lipid regulation of the glucagon receptor family.

The glucagon receptor family are typical class B1 G protein-coupled receptors (GPCRs) with important roles in metabolism, including the control of pancreas, brain, and liver function. As proteins with seven transmembrane domains, GPCRs are intimately in contact with lipid bilayers and therefore can be putatively regulated by interactions with their lipidic components, including cholesterol, sphingolipids, and other lipid species. Additionally, these receptors, as well as the agonists they bind to, can undergo lipid modifications, which can influence their binding capacity and/or elicit modified or biased signalling profiles. While the effect of lipids, and in particular cholesterol, has been widely studied for other GPCR classes, information about their role in regulating the glucagon receptor family is only beginning to emerge. Here we summarise our current knowledge on the effects of cholesterol modulation of glucagon receptor family signalling and trafficking profiles, as well as existing evidence for specific lipid-receptor binding and indirect effects of lipids via lipid modification of cognate agonists. Finally, we discuss the different methodologies that can be employed to study lipid-receptor interactions and summarise the importance of this area of investigation to increase our understanding of the biology of this family of metabolically relevant receptors.

The DESI one-per cent survey: exploring the halo occupation distribution of luminous red galaxies and quasi-stellar objects with AbacusSummit

ABSTRACT We present the first comprehensive halo occupation distribution (HOD) analysis of the Dark Energy Spectroscopic Instrument (DESI) One-Percent Survey luminous red galaxy (LRG) and Quasi Stellar Object (QSO) samples. We constrain the HOD of each sample and test possible HOD extensions by fitting the redshift-space galaxy 2-point correlation functions in 0.15 < r < 32 h−1 Mpc in a set of fiducial redshift bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model templates and forward model galaxy clustering with the AbacusHOD package. We achieve good fits with a standard HOD model with velocity bias, and we find no evidence for galaxy assembly bias or satellite profile modulation at the current level of statistical uncertainty. For LRGs in 0.4 < z < 0.6, we infer a satellite fraction of $f_\mathrm{sat} = 11\pm 1~{y{\ \mathrm{per\,cent}}}$, a mean halo mass of $\log _{10}\overline{M}_h/M_\odot =13.40^{+0.02}_{-0.02}$, and a linear bias of $b_\mathrm{lin} = 1.93_{-0.04}^{+0.06}$. For LRGs in 0.6 < z < 0.8, we find $f_\mathrm{sat}=14\pm 1~{{\ \mathrm{per\,cent}}}$, $\log _{10}\overline{M}_h/M_\odot =13.24^{+0.02}_{-0.02}$, and $b_\mathrm{lin}=2.08_{-0.03}^{+0.03}$. For QSOs, we infer $f_\mathrm{sat}=3^{+8}_{-2}\mathrm{per\,cent}$, $\log _{10}\overline{M}_h/M_\odot = 12.65^{+0.09}_{-0.04}$, and $b_\mathrm{lin} = 2.63_{-0.26}^{+0.37}$ in redshift range 0.8 < z < 2.1. Using these fits, we generate a large suite of high fidelity galaxy mocks, forming the basis of systematic tests for DESI Y1 cosmological analyses. We also study the redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealling significant and interesting trends in mean halo mass, linear bias, and satellite fraction.

The GLP-1R as a model for understanding and exploiting biased agonism in next-generation medicines.

The glucagon-like peptide 1 receptor (GLP-1R) is a class B G protein-coupled receptor (GPCR) that emerged as a pharmacologic target in cardiometabolic disease, including diabetes and obesity, over 30 years ago. The subsequent widespread clinical use of GLP-1R agonists, including exenatide, liraglutide, and semaglutide, has made the GLP-1R a preeminent model for understanding basic GPCR biology, including the emergent field of biased agonism. Recent data demonstrate that the dual GLP-1R/glucose dependent insulinotropic polypeptide receptor (GIPR) agonist tirzepatide exhibits a biased signaling profile characterized by preferential Gαs activation over β-arrestin recruitment, which appears to contribute to its insulinotropic and body-weight reducing effects in preclinical models. This constitutes a major finding in which nuanced, mechanistic receptor signaling dynamics in vitro mediate real-world clinical differentiation within a drug class. Because of the striking bench-top-to-bed side relevance of this biased signaling phenomenon, we have undertaken a review of the emerging data detailing biased agonism at the GLP-1R. In this review, we introduce the core concept of biased agonism followed by a detailed consideration of the key mechanisms, including ligand-mediated bias, receptor-mediated bias, and systems/cell-type bias. Current industry programs are largely, if not entirely, focused on developing biased ligands, and so we have dedicated a section of the review to a brief meta-analysis of compounds reported to drive biased signaling, with a consideration of the structural determinants of receptor-ligand interactions. In this work, we aim to assess the current knowledge regarding signaling bias at the GLP-1R and how these ideas might be leveraged in future optimization.

Modeling the Effect of Spatial Structure on Solid Tumor Evolution and Circulating Tumor DNA Composition.

Circulating tumor DNA (ctDNA) monitoring, while sufficiently advanced to reflect tumor evolution in real time and inform cancer diagnosis, treatment, and prognosis, mainly relies on DNA that originates from cell death via apoptosis or necrosis. In solid tumors, chemotherapy and immune infiltration can induce spatially variable rates of cell death, with the potential to bias and distort the clonal composition of ctDNA. Using a stochastic evolutionary model of boundary-driven growth, we study how elevated cell death on the edge of a tumor can simultaneously impact driver mutation accumulation and the representation of tumor clones and mutation detectability in ctDNA. We describe conditions in which invasive clones are over-represented in ctDNA, clonal diversity can appear elevated in the blood, and spatial bias in shedding can inflate subclonal variant allele frequencies (VAFs). Additionally, we find that tumors that are mostly quiescent can display similar biases but are far less detectable, and the extent of perceptible spatial bias strongly depends on sequence detection limits. Overall, we show that spatially structured shedding might cause liquid biopsies to provide highly biased profiles of tumor state. While this may enable more sensitive detection of expanding clones, it could also increase the risk of targeting a subclonal variant for treatment. Our results indicate that the effects and clinical consequences of spatially variable cell death on ctDNA composition present an important area for future work.

Alter codon bias of the P. pastoris genome to overcome a bottleneck in codon optimization strategy development and improve protein expression

Apart from its role in translation, codon bias is also an important mechanism to regulate mRNA levels. The traditional frequency-based codon optimization strategy is rather efficient in organisms such as N. crassa, but much less in yeast P. pastoris which is a popular host for heterologous protein expression. This is because that unlike N. crassa, the preferred codons of P. pastoris are actually AU-rich and hence codon optimization for extremely low GC content comes with issues of pre-mature transcriptional termination or low RNA stability in spite of translational advantages. To overcome this bottleneck, we focused on three reporter genes in P. pastoris first and confirmed the great advantage of GC-prone codon optimization on mRNA levels. Then we altered the codon bias profile of P. pastoris by introducing additional rare tRNA gene copies. Prior to that we constructed IPTG-regulated tRNA species to enable chassis cells to switch between different codon bias status. As demonstrated again with reporter genes, protein yield of luc and 0788 was successfully increased by 4–5 folds in chassis cells. In summary, here we provide an alternative codon optimization strategy for genes with unsatisfactory performance under traditional codon frequency-based optimization.

A News Media Bias and Factuality Profiling Framework Assisted by Modeling Correlation

A News Media Bias and Factuality Profiling Framework Assisted by Modeling Correlation

Biased polar question forms in Sign Language of the Netherlands (NGT)

We identify several polar question forms in Sign Language of the Netherlands (NGT)through a production experiment in which we manipulate two types of biases: (i) theprior expectations of the person asking the question, and (ii) the evidence available inthe immediate context of utterance. Our analysis in the present paper focuses on formsinvolving headshake. We find that in some cases headshake expresses negation, as expected,but in other cases it fulfils another function, namely, it is part of a sentence-finalphrase either expressing uncertainty or signalling a request for a response from the addressee,or possibly both at the same time. We further observe that each question formhas a distinct ‘bias profile’, indicating a certain combination of prior expectations andcontextual evidence. Besides these empirical findings, our study also makes a methodologicalcontribution: our experimental design could be used in future work to identifypolar question forms with different bias profiles in sign languages other than NGT, aswell as visual cues accompanying polar questions with different bias profiles in spokenlanguages.

Nonfucosylation of an anti-TIGIT antibody enhances FcγR engagement, driving innate immune activation and antitumor activity.

TIGIT is an immune checkpoint receptor expressed on activated and memory T cells, immunosuppressive T regulatory cells, and natural killer (NK) cells. TIGIT has emerged as an attractive target for antitumor therapies, due to its proposed immunosuppressive effects on lymphocyte function and T cell activation. We generated an anti-TIGIT monoclonal antibody (mAb) that binds with high affinity to human, non-human primate, and murine TIGIT and through multiple experimental methodologies demonstrated that checkpoint blockade alone is insufficient for antitumor activity. Generating anti-TIGIT mAbs with various Fc backbones we show that muting the Fc-Fcγ receptor (FcγR) interaction failed to drive antitumor activity, while mAbs with Fc functional backbones demonstrate substantial antitumor activity, mediated through activation of antigen-presenting cells (APCs), T cell priming, and NK-mediated depletion of suppressive Tregs and exhausted T cells. Further, nonfucosylation of the Fc backbone resulted in enhanced immune responses and antitumor activity relative to the intact IgG1 backbone. The improved activity correlated with the biased FcγR interaction profile of the nonfucosylated anti-TIGIT mAb, which supports that FcγRIIIa binding with decreased FcγRIIb binding favorably activates APCs and enhances tumor-specific CD8+ T cell responses. The anti-TIGIT mAbs with intact FcγR interacting backbones also demonstrated synergistic enhancement of other standard antitumor treatments, including anti-PD-1 treatment and a model monomethyl auristatin E antibody-drug conjugate. These findings highlight the importance of the anti-TIGIT mAb's Fc backbone to its antitumor activity and the extent to which this activity can be enhanced through nonfucosylation of the backbone.

Decadal variability of oxygen uptake, export, and storage in the Labrador Sea from observations and CMIP6 models

The uptake of dissolved oxygen from the atmosphere via air-sea gas exchange and its physical transport away from the region of uptake are crucial for supplying oxygen to the deep ocean. This process takes place in a few key regions that feature intense oxygen uptake, deep water formation, and physical oxygen export. In this study we analyze one such region, the Labrador Sea, utilizing the World Ocean Database (WOD) to construct a 65–year oxygen content time series in the Labrador Sea Water (LSW) layer (0–2200 m). The data reveal decadal variability associated with the strength of deep convection, with a maximum anomaly of 27 mol m–2 in 1992. There is no long-term trend in the time series, suggesting that the mean oxygen uptake is balanced by oxygen export out of the region. We compared the time series with output from nine models of the Ocean Model Intercomparison Project phase 1 in the Climate Model Intercomparison Project phase 6, (CMIP6-OMIP1), and constructed a “model score” to evaluate how well they match oxygen observations. Most CMIP6-OMIP1 models score around 50/100 points and the highest score is 57/100 for the ensemble mean, suggesting that improvements are needed. All of the models underestimate the maximum oxygen content anomaly in the 1990s. One possible cause for this is the representation of air-sea gas exchange for oxygen, with all models underestimating the mean uptake by a factor of two or more. Unrealistically deep convection and biased mean oxygen profiles may also contribute to the mismatch. Refining the representation of these processes in climate models could be vital for enhanced predictions of deoxygenation. In the CMIP6-OMIP1 multi-model mean, oxygen uptake has its maximum in 1980–1992, followed by a decrease in 1994–2006. There is a concurrent decrease in export, but oxygen storage also changes between the two periods, with oxygen accumulated in the first period and drained out in the second. Consequently, the change in oxygen export (5%) is much less than that in uptake (28%), suggesting that newly ventilated LSW which remains in the formation region acts to buffer the linkage between air-sea gas exchange and oxygen export.

Contingent administration of typical and biased kappa opioid agonists reduces cocaine and oxycodone choice in a drug vs. food choice procedure in male rhesus monkeys.

Combinations of mu and kappa-opioid receptor (KOR) agonists have been proposed as analgesic formulations with reduced abuse potential. The feasibility of this approach has been increased by the development of KOR agonists with biased signaling profiles that produce KOR-typical antinociception with fewer KOR-typical side effects. The present study determined if the biased KOR agonists, nalfurafine and triazole 1.1, could reduce choice for oxycodone in rhesus monkeys as effectively as the typical KOR agonist, salvinorin A. Adult male rhesus monkeys (N = 5) responded under a concurrent schedule of food delivery and intravenous cocaine injections (0.018mg/kg/injection). Once trained, cocaine (0.018mg/kg/injection) or oxycodone (0.0056mg/kg/injection) was tested alone or in combination with contingent injections of salvinorin A (0.1-3.2µg/kg/injection), nalfurafine (0.0032-0.1µg/kg/injection), triazole 1.1 (3.2-100.0µg/kg/injection), or vehicle. In each condition, the cocaine or oxycodone dose, as well as the food amount, was held constant across choice components, while the dose of the KOR agonist was increased across choice components. Cocaine and oxycodone were chosen over food on more than 80% of trials when administered alone or contingently with vehicle. When KOR agonists were administered contingently with either cocaine or oxycodone, drug choice decreased in a dose-dependent manner. Salvinorin A and triazole 1.1 decreased drug-reinforcer choice without altering total trials completed (i.e., choice allocation shifted to food), while nalfurafine dose dependently decreased total trials completed. These results demonstrate that salvinorin A and triazole 1.1, but not nalfurafine, selectively reduce cocaine and oxycodone self-administration independent of nonspecific effects on behavior, suggesting that G-protein bias does not appear to be a moderating factor in this outcome. Triazole 1.1 represents an important prototypical compound for developing novel KOR agonists as deterrents for prescription opioid abuse.

Neutralizing antibodies with neurotropic factor treatment maintain neurodevelopmental gene expression upon exposure to human cytomegalovirus.

Human cytomegalovirus (HCMV) infection is the leading cause of non-heritable birth defects worldwide. HCMV readily infects the early progenitor cell population of the developing brain, and we have found that infection leads to significantly downregulated expression of key neurodevelopmental transcripts. Currently, there are no approved therapies to prevent or mitigate the effects of congenital HCMV infection. Therefore, we used human-induced pluripotent stem cell-derived organoids and neural progenitor cells to elucidate the glycoproteins and receptors used in the viral entry process and whether antibody neutralization was sufficient to block viral entry and prevent disruption of neurodevelopmental gene expression. We found that blocking viral entry alone was insufficient to maintain the expression of key neurodevelopmental genes, but neutralization combined with neurotrophic factor treatment provided robust protection. Together, these studies offer novel insight into mechanisms of HCMV infection in neural tissues, which may aid future therapeutic development.

On further delimiting the space of bias profiles for polar interrogatives

On further delimiting the space of bias profiles for polar interrogatives

The importance of glucose-dependent insulinotropic polypeptide receptor activation for the effects of tirzepatide.

Tirzepatide is a unimolecular co-agonist of the glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) receptors recently approved for the treatment of type 2 diabetes by the US Food and Drug Administration and the European Medicine Agency. Tirzepatide treatment results in an unprecedented improvement of glycaemic control and lowering of body weight, but the contribution of the GIP receptor-activating component of tirzepatide to these effects is uncertain. In this review, we present the current knowledge about the physiological roles of the incretin hormones GLP-1 and GIP, their receptors, and previous results of co-targeting the two incretin hormone receptors in humans. We also analyse the molecular pharmacological, preclinical and clinical effects of tirzepatide to discuss the role of GIP receptor activation for the clinical effects of tirzepatide. Based on the available literature on the combination of GLP-1 and GIP receptor activation, tirzepatide does not seem to have a classical co-activating mode of action in humans. Rather, in vitro studies of the human GLP-1 and GIP receptors reveal a biased GLP-1 receptor activation profile and GIP receptor downregulation. Therefore, we propose three hypotheses for the mode of action of tirzepatide, which can be addressed in future, elaborate clinical trials.