Pindolol potentiates the antidepressant effect of venlafaxine by inhibiting 5-HT1A receptor in DRN neurons of mice

Fucoxanthin restructures the gut microbiota and metabolic functions of non-obese individuals in an in vitro fermentation model

Fucoxanthin, a carotenoid exclusively derived from algae, exerts its bioactivities with the modulation of the gut microbiota in mice. However, mechanisms through which fucoxanthin regulates the gut microbiota and its derived metabolites/metabolism in humans remain unclear. In this study, we investigated the effects of fucoxanthin on the gut microbiota and metabolism of non-obese individuals using an in vitro simulated digestion-fermentation cascade model. The results showed that about half of the fucoxanthin was not absorbed in the intestine, thus reaching the colon. The gut microbiota from fecal samples underwent significant changes after 48 or 72 hours in vitro fermentation. Specifically, fucoxanthin significantly enhanced the relative abundance of Bacteroidota and Parabacteroides, leading to improved functions of the gut microbiota in its development, glycan biosynthesis and metabolism as well as in improving the digestive system, endocrine system and immune system. The recovery of fucoxanthin during fermentation showed a decreasing trend with the slight bio-conversion of fucoxanthinol. Notably, fucoxanthin supplementation significantly altered metabolites, especially bile acids and indoles in the simulated human gut ecosystem. Correlation analysis indicated the involvement of the gut microbiota in the manipulation of these metabolites by fucoxanthin. Moreover, all these altered metabolites revealed the improvement in the capacity of fucoxanthin in manipulating gut metabolism, especially lipid metabolism. Overall, fucoxanthin determinedly reshaped the gut microbiota and metabolism, implying its potential health benefits in non-obese individuals.

Enhancing antifungal properties of chitosan by attaching isatin-piperazine-sulfonyl-acetamide pendant groups via novel imidamide linkage

World health organization listed fungi as priority pathogens in 2022 to counter their adverse effects on human well-being. The use of antimicrobial biopolymers is a sustainable alternative to toxic antifungal agents. In this study, we explore chitosan as an antifungal agent by grafting a novel compound N-(4-((4-((isatinyl)methyl)piperazin-1-yl)sulfonyl)phenyl) acetamide (IS). The acetimidamide linkage of IS to chitosan herein was confirmed by ¹³C NMR and is a new branch in chitosan pendant group chemistry. The modified chitosan films (ISCH) were studied using thermal, tensile, and spectroscopic methods. The ISCH derivatives strongly inhibit fungal pathogens of agricultural and human importance, namely Fusarium solani, Colletotrichum gloeosporioides, Myrothecium verrucaria, Penicillium oxalicum, and Candida albicans. ISCH80 showed an IC₅₀ value of 0.85 μg/ml against M. verrucaria and ISCH100 with IC₅₀ of 1.55 μg/ml is comparable to the commercial antifungal IC₅₀ values of Triadiamenol (3.6 μg/ml) and Trifloxystrobin (3 μg/ml). Interestingly, the ISCH series remained non-toxic up to 2000 μg/ml against L929 mouse fibroblast cells. The ISCH series showed long-standing antifungal action, superior to our lowest observed antifungal IC₅₀ values of plain chitosan and IS at 12.09 μg/ml and 3.14 μg/ml, respectively. ISCH films are thus suitable for fungal inhibition in an agricultural setting or food preservation.

A novel method for drug-target interaction prediction based on graph transformers model

BACKGROUND

Drug-target interactions (DTIs) prediction becomes more and more important for accelerating drug research and drug repositioning. Drug-target interaction network is a typical model for DTIs prediction. As many different types of relationships exist between drug and target, drug-target interaction network can be used for modeling drug-target interaction relationship. Recent works on drug-target interaction network are mostly concentrate on drug node or target node and neglecting the relationships between drug-target.

RESULTS

We propose a novel prediction method for modeling the relationship between drug and target independently. Firstly, we use different level relationships of drugs and targets to construct feature of drug-target interaction. Then, we use line graph to model drug-target interaction. After that, we introduce graph transformer network to predict drug-target interaction.

CONCLUSIONS

This method introduces a line graph to model the relationship between drug and target. After transforming drug-target interactions from links to nodes, a graph transformer network is used to accomplish the task of predicting drug-target interactions.

Risks of Digestive System Side-Effects of Selective Serotonin Reuptake Inhibitors in Patients with Depression: A Network Meta-Analysis

Purpose

Selective serotonin reuptake inhibitors (SSRIs) are the preferred treatments for depression. The most common adverse drug reactions are symptoms involving the digestive system, leading to low compliance in patients with depression. Therefore, it is important to assess the safety of SSRIs with respect to the digestive system. Several meta-analyses have compared the risks of digestive side effects of SSRIs and other antidepressants. We aimed to compare the risks of various SSRIs (fluoxetine, escitalopram, citalopram, paroxetine, and sertraline) for adverse reactions of the digestive system.

Methods

Systematic searches returned 30 randomized controlled trials (n = 5004) of five antidepressants and placebos.

Results

Fluoxetine had the lowest probability of digestive side effects, ranking fifth at 0.548. Sertraline had the highest probability of digestive side effects, with a probability of 0.611. For gastrointestinal tolerability, escitalopram was better than paroxetine (odds ratio [OR] =0.62, 95% confidence interval [CI] 0.43–0.87) and sertraline (OR=0.56, 95% CI 0.32–0.99).

Conclusion

Fluoxetine exhibited distinct advantages compared to other SSRIs, while sertraline had the greatest likelihood of digestive system side effects. These findings will help doctors understand the relative advantages of various antidepressants.

Anxiolytic and antidepressant-like effects of monoterpene tetrahydrolinalool and in silico approach of new potential targets

INTRODUCTION- The drugs currently available for treatment of anxiety and depression act through modulation of the neurotransmission systems involved in the neurobiology of the disorder, yet they of-ten present side effects, which can impair patient adherence to treatment. METHOD- This, has driven the search for new molecules with anxiolytic and antidepressant potential. Aromatic plants are rich in essential oils, and their chemical constituents, such as monoterpenes, are be-ing studied for these disorders. This study aims to evaluate the anxiolytic and antidepressant-like poten-tial of the monoterpene tetrahydrolinalool in in vivo animal models, and review pharmacological targets with validation through molecular docking. Male Swiss mice (Mus musculus) were treated with THL (37.5-600 mg kg-1 p.o.) and submitted to the elevated plus maze, open field, rota rod, and forced swim tests. In the elevated plus-maze, THL at doses of 37.5 and 75 mg kg-1 induced a significant increase in the percentage of entries (72.7 and 64.3% respectively), and lengths of stay (80.3 and 76.8% respective-ly) in the open arms tests. RESULT- These doses did not compromise locomotor activity or motor coordination in the animals. In the open field, rota rod tests, and the forced swimming model, treatment with THL significantly reduced immobility times at doses of 150, 300, and 600 mg kg-1, and by respective percentages of 69.3, 60.9 and 68.7%. CONCLUSION- In molecular docking assay, which investigated potential targets, THL presented sat-isfactory energy values for: nNOs, SGC, IL-6, 5-HT1A, NMDAr, and D1. These demonstrate the po-tential of THL (a derivative of natural origin) in in vivo and in silico models, making it a drug candidate.

Biased agonism in drug discovery: Is there a future for biased 5-HT1A receptor agonists in the treatment of neuropsychiatric diseases?

Serotonin (5-HT) is one of the fundamental neurotransmitters that contribute to the information essential for an organism's normal, physiological function. Serotonin acts centrally and systemically. The 5-HT_1A receptor is the most widespread serotonin receptor, and participates in many brain-related disorders, including anxiety, depression, and cognitive impairments. The 5-HT_1A receptor can activate several different biochemical pathways and signals through both G protein-dependent and G protein-independent pathways. Preclinical experiments indicate that distinct signaling pathways in specific brain regions may be crucial for antidepressant-like, anxiolytic-like, and procognitive responses. Therefore, the development of new ligands that selectively target a particular signaling pathway(s) could open new possibilities for more effective and safer pharmacotherapy. This review discusses the current state of preclinical studies focusing on the concept of functional selectivity (biased agonism) regarding the 5-HT_1A receptor and its role in antidepressant-like, anxiolytic-like, and procognitive regulation. Such work highlights not only the differential effects of targeted autoreceptors, vs. heteroreceptors, but also the importance of targeting specific downstream intracellular signaling processes, thereby enhancing favorable over unfavorable signaling activation.