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Introduction Objective Methods Results Conclusions Primary premature ejaculation (PPE) is a common male neurobiological disorder. Currently, there is consensus that the impairment in central serotonin (5‐HT) neurotransmission constitutes a key pathogenic factor in PPE. Selective serotonin reuptake inhibitors (SSRIs) serve as the primary pharmacological intervention; however, a comprehensive elucidation of their mechanism of action remains incomplete. Owing to significant individual variability in efficacy, SSRIs exhibit a high discontinuation rate. Hence, there is an urgent need to address the selection of SSRIs for PPE treatment.This study aims to investigate the characteristics of tryptophan (TRP) metabolism in patients with PPE and to assess its influence on the efficacy of SSRIs.The exploratory study included a total of 16 patients with PPE and 16 control subjects who were healthy men without any sexual dysfunction. Upon enrollment in the study, all participants underwent a thorough medical history review and physical examination. Subsequently, their serum levels of TRP, its metabolites, large neutral amino acids (LNAAs), and metabolite ratios were assessed using a liquid chromatography–mass spectrometry (LC–MS) assay. After a period of 4 weeks of dapoxetine treatment, all patients with PPE underwent reassessment using the Premature Ejaculation Diagnostic Tool (PEDT) score and intravaginal ejaculatory latency time (IELT) test.The ratio of serum TRP to other LNAAs (TRP/LNAAs) in patients with PPE was found to be significantly lower compared to the control group (P < 0.05). Conversely, the ratio of kynurenine to TRP (KYN/TRP) was observed to be significantly higher in the PPE patients compared to the control group (P < 0.05). Including the serum TRP/LNAAs ratio and KYN/TRP ratio in the prediction model yielded the highest prediction efficiency for PPE. There was a significant negative correlation between the ratio of TRP/LNAAs before the treatment and the IELT after 4 weeks of the treatment. Additionally, there was a significant positive correlation observed between the ratio of TRP/LNAAs before the treatment and the PEDT score after 4 weeks of the treatment.This study demonstrates that the reduction in the TRP/LNAAs ratio and the elevation of the KYN/TRP ratio are significant characteristics associated with PPE. These findings suggest that diminished tryptophan availability in the brain and the activation of the kynurenine (KYN) pathway may play a role in the pathogenesis of PPE. The TRP/LNAAs ratio has potential as a reliable indicator of central serotonin (5‐HT) levels. Considering the TRP/LNAAs ratio when selecting SSRIs for the treatment of PPE may enhance the response rate of this medication. [ABSTRACT FROM AUTHOR]

Biointerfacing nanomaterials with cell membranes has been successful in the functionalization of nanoparticles or nanovesicles, but microbubble functionalization remains challenging due to the unique conformation of the lipid monolayer structure at the gas-liquid interface that provides insufficient surfactant activity. Here, we describe a strategy to rationally regulate the surfactant activity of platelet membrane vesicles by adjusting the ratio of proteins to lipids through fusion with synthetic phospholipids (i.e., liposomes). A "platesome" with the optimized protein-to-lipid ratio can be assembled at the gas-liquid interface in the same manner as pulmonary surfactants to stabilize a microsized gas bubble. Platesome microbubbles (PMBs) inherited 61.4 % of the platelet membrane vesicle proteins and maintained the active conformation of integrin αIIbβ3 without the talin 1 for fibrin binding. We demonstrated that the PMBs had good stability, long circulation, and superior functionality both in vitro and in vivo. Moreover, by molecular ultrasound imaging, the PMBs provide up to 11.8 dB of ultrasound signal-to-noise ratio enhancement for discriminating between acute and chronic thrombi. This surface tension regulating strategy may provide a paradigm for biointerfacing microbubbles with cell membranes, offering a potential new approach for the construction of molecular ultrasound contrast agents for the diagnosis of different diseases., (© 2024 Wiley-VCH GmbH.)

Introduction: Burns are a global public health problem. Major burns can stimulate the body to enter a stress state, thereby increasing the risk of infection and adversely affecting the patient's prognosis. Recently, it has been discovered that cuproptosis, a form of cell death, is associated with various diseases. Our research aims to explore the molecular clusters associated with cuproptosis in major burns and construct predictive models., Methods: We analyzed the expression and immune infiltration characteristics of cuproptosis-related factors in major burn based on the GSE37069 dataset. Using 553 samples from major burn patients, we explored the molecular clusters based on cuproptosis-related genes and their associated immune cell infiltrates. The WGCNA was utilized to identify cluster-specific genes. Subsequently, the performance of different machine learning models was compared to select the optimal model. The effectiveness of the predictive model was validated using Nomogram, calibration curves, decision curves, and an external dataset. Finally, five core genes related to cuproptosis and major burn have been was validated using RT-qPCR., Results: In both major burn and normal samples, we determined the cuproptosis-related genes associated with major burns through WGCNA analysis. Through immune infiltrate profiling analysis, we found significant immune differences between different clusters. When K=2, the clustering number is the most stable. GSVA analysis shows that specific genes in cluster 2 are closely associated with various functions. After identifying the cross-core genes, machine learning models indicate that generalized linear models have better accuracy. Ultimately, a generalized linear model for five highly correlated genes was constructed, and validation with an external dataset showed an AUC of 0.982. The accuracy of the model was further verified through calibration curves, decision curves, and modal graphs. Further analysis of clinical relevance revealed that these correlated genes were closely related to time of injury., Conclusion: This study has revealed the intricate relationship between cuproptosis and major burns. Research has identified 15 cuproptosis-related genes that are associated with major burn. Through a machine learning model, five core genes related to cuproptosis and major burn have been selected and validated., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Xiong, Hong, Liao, Yang, Jiang, Jing, Huang, Fu and Zhu.)