Negative cooperativity across 1-adrenoceptor homodimers provides insights into the nature of the secondary low-affinity CGP 12177 1-adrenoceptor binding conformation

At the β1-adrenoceptor, CGP 12177 potently antagonizes agonist responses at the primary high-affinity catecholamine conformation while also exerting agonist effects of its own through a secondary low-affinity conformation. A recent mutagenesis study identified transmembrane region (TM)4 of the β1-adrenoceptor as key for this low-affinity conformation. Others suggested that TM4 has a role in β1-adrenoceptor oligomerization. Here, assessment of the dissociation rate of a fluorescent analog of CGP 12177 [bordifluoropyrromethane-tetramethylrhodamine-(±)CGP 12177 (BODIPY-TMR-CGP)] at the human β1-adrenoceptor expressed in Chinese hamster ovary cells revealed negative cooperative interactions between 2 distinct β1-adrenoceptor conformations. The dissociation rate of 3 nM BODIPY-TMR-CGP was 0.09 ± 0.01 min−1 in the absence of competitor ligands, and this was enhanced 2.2- and 2.1-fold in the presence of 1 µM CGP 12177 and 1 µM propranolol, respectively. These effects on the BODIPY-TMR-CGP dissociation rate were markedly enhanced in β1-adrenoceptor homodimers constrained by bimolecular fluorescence complementation (9.8- and 9.9-fold for 1 µM CGP 12177 and 1 µM propranolol, respectively) and abolished in β1-adrenoceptors containing TM4 mutations vital for the second conformation pharmacology. This study suggests that negative cooperativity across a β1-adrenoceptor homodimer may be responsible for generating the low-affinity pharmacology of the secondary β1-adrenoceptor conformatio

A Full Pharmacological Analysis of the Three Turkey β-Adrenoceptors and Comparison with the Human β-Adrenoceptors

There are three turkey β-adrenoceptors: the original turkey β-adrenoceptor from erythrocytes (tβtrunc, for which the X-ray crystal structure has recently been determined), tβ3C and tβ4C-receptors. This study examined the similarities and differences between these avian receptors and mammalian receptors with regards to binding characteristics and functional high and low affinity agonist conformations.Stable cell lines were constructed with each of the turkey β-adrenoceptors and 3H-CGP12177 whole cell binding, CRE-SPAP production and (3)H-cAMP accumulation assays performed. It was confirmed that the three turkey β-adrenoceptors are distinct from each other in terms of amino acid sequence and binding characteristics. The greatest similarity of any of the turkey β-adrenoceptors to human β-adrenoceptors is between the turkey β3C-receptor and the human β2-adrenoceptor. There are pharmacologically distinct differences between the binding of ligands for the tβtrunc and tβ4C and the human β-adrenoceptors (e.g. with CGP20712A and ICI118551). The tβtrunc and tβ4C-adrenoceptors appear to exist in at least two different agonist conformations in a similar manner to that seen at both the human and rat β1-adrenoceptor and human β3-adrenoceptors. The tβ3C-receptor, similar to the human β2-adrenoceptor, does not, at least so far, appear to exist in more than one agonist conformation.There are several similarities, but also several important differences, between the recently crystallised turkey β-adrenoceptor and the human β-adrenoceptors. These findings are important for those the field of drug discovery using the recently structural information from crystallised receptors to aid drug design. Furthermore, comparison of the amino-acid sequence for the turkey and human adrenoceptors may therefore shed more light on the residues involved in the existence of the secondary β-adrenoceptor conformation

9-PAHSA displays a weak anti-inflammatory potential mediated by specific antagonism of chemokine G protein-coupled receptors

Introduction: 9-PAHSA belongs to a class of endogenous mammalian bioactive lipids, fatty acid esters of hydroxy fatty acids (FAHFA), that are present in circulation at nanomolar concentrations in mice and humans. Published preclinical data suggest beneficial effects of 9-PAHSA treatment on glucose metabolism as well as modulation of immune function. However, receptor molecules with high affinity towards these lipids have not been identified so far.Methods: In a broad screen of a panel of G protein-coupled receptors (GPCRs) we discovered that 9-PAHSA displays antagonist activity with an IC50 in the micromolar range on selected chemokine receptors, namely, CCR6, CCR7, CXCR4, and CXCR5. The potential immunomodulatory activities in a human cellular model of innate immunity were then investigated.Results and discussion: In our in vitro experiments, a weak anti-inflammatory potential for high concentrations of 9-PAHSA (10–100 µM) could be detected, as treatment reduced the LPS-induced secretion of certain chemokines, such as CXCL10, MIP-1 beta and MCP. Regarding metabolic effects, we re-investigated 9-PAHSA on glucose metabolism and insulin sensitivity in vitro and in mice confirming conclusions from our earlier study that FAHFAs lack glucoregulatory activity following an acute treatment. In conclusion, the specific interactions with a subset of chemokine receptors may contribute to weak anti-inflammatory properties of 9-PAHSA, but further studies are needed to confirm its in anti-inflammatory potential in vivo

High-throughput mediation analysis of human proteome and metabolome identifies mediators of post-bariatric surgical diabetes control

To improve the power of mediation in high-throughput studies, here we introduce High-throughput mediation analysis (Hitman), which accounts for direction of mediation and applies empirical Bayesian linear modeling. We apply Hitman in a retrospective, exploratory analysis of the SLIMM-T2D clinical trial in which participants with type 2 diabetes were randomized to Roux-en-Y gastric bypass (RYGB) or nonsurgical diabetes/weight management, and fasting plasma proteome and metabolome were assayed up to 3 years. RYGB caused greater improvement in HbA1c, which was mediated by growth hormone receptor (GHR). GHR’s mediation is more significant than clinical mediators, including BMI. GHR decreases at 3 months postoperatively alongside increased insulin-like growth factor binding proteins IGFBP1/BP2; plasma GH increased at 1 year. Experimental validation indicates (1) hepatic GHR expression decreases in post-bariatric rats; (2) GHR knockdown in primary hepatocytes decreases gluconeogenic gene expression and glucose production. Thus, RYGB may induce resistance to diabetogenic effects of GH signaling

Deepfake Generation and Detection: A Survey

Advancements in the field of deep learning have revolutionized various domains, demonstrating significant success in solving complex problems, ranging from big data analytics to computer vision and human-level control. The evolution of deep learning algorithms, particularly in the context of Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), has played a pivotal role in pushing the boundaries of artificial intelligence. Deep learning, with its ability to automatically learn intricate patterns and representations from vast amounts of data, has found application in the creation of deepfake technology. Deepfakes are synthetic media, including images and videos, generated through sophisticated algorithms that utilize deep learning techniques. These algorithms enable the creation of hyper-realistic forgeries that can be indistinguishable from authentic content, posing serious threats to privacy, democracy, and national security. This paper conducts a thorough examination of the creation and detection technologies associated with deepfakes, employing deep learning approaches. We delve into an extensive analysis of various techniques and their application in the detection of deepfakes. This comprehensive study is poised to benefit researchers in the field by covering state-of-the-art methods for identifying deepfake videos or images within social contexts. Furthermore, our work facilitates meaningful comparisons with existing research, providing detailed descriptions of the latest methods and datasets utilized in this rapidly evolving domain. Through this contribution, we aim to aid the development of new and more robust methods to address the growing challenges posed by deepfake technologies. Keywords—Deep learning, Deepfake technology, Generative Adversarial Networks (GANs), Synthetic media, Detection technologies, Privac