Agatolimod

Preservatives are primarily used for their antimicrobial properties and form an important component of food, cosmetic, and drug formulations. The efficacy of preservatives depends on various factors, which include the bacterial membrane composition and the interaction between components of a specific formulation. Molecules such as phenoxyethanol (POE), caprylylglycol (CPG), and methylparaben (MEP) are widely used as preservatives in the food and cosmetic industries; however, a molecular understanding of their interactions with surfactants and the kinetics of membrane partitioning remains unexplored. In this study, coarse-grained molecular dynamics simulations were carried out to evaluate and quantify the kinetics of membrane partitioning for preservatives and surfactants in the Escherichia coli inner phospholipid membrane. We propose a mass-transfer-based model to determine membrane partitioning kinetics. Faster kinetics were observed for first-order partitioning of POE and MEP (τ ∼ 0.01 μs) when compared with zeroth-order kinetics (τ ∼ 0.1 μs) for CPG. In contrast, surfactants such as sodium laureth sulfate (SLES) and cocamidopropyl betaine (CAPB) follow zeroth-order membrane partitioning kinetics with significantly higher time constants (1.5-10 μs). Interestingly, zeroth-order kinetics occurred when micellar aggregates were present, and the rate-controlling step was the slow rate of release of single molecules from the aggregate, in comparison to faster membrane uptake kinetics. Using a sequential micellar breakup model with single surfactant release dynamics, we analytically recover this unique zeroth-order membrane partitioning kinetics. In preservative-surfactant mixtures, the kinetics of preservative partitioning were found to decrease by a factor of 2-10. Significantly, the equilibrium membrane saturation coefficients for both preservatives and surfactant remained invariant in the mixtures due to the wide separation of partitioning time scales for the surfactants and preservatives. The kinetic models developed in this study can be used to quantify membrane partitioning of preservatives and understand the influence of surfactants in specific formulations.

Objective: To explore a novel strategy for treating immunologically "cold" lung tumors by combining neoantigen-pulsed dendritic cell (DC) vaccines with CpG. Methods: LLC1 cells were analyzed by whole-exome sequencing and RNA sequencing. Tumor-specific nonsynonymous mutations were identified using RNA sequencing data, and candidate neoantigens were screened by predicting their binding affinity to major histocompatibility complex molecules using NetMHCpan v4.0 and NetMHCⅡpan v3.2. Neoantigens LLC1-M01, LLC1-M02, LLC1-M03, LLC1-M04, and LLC1-M05 were synthesized via Fmoc solid-phase peptide synthesis. Candidate neoantigens were subcutaneously inoculated into C57BL/6 mice. Neoantigen immunogenicity was assessed using flow cytometry, and interferon-gamma (IFN-γ) secretion by effector T cells was measured via enzyme-linked immunospot assay. A neoantigen-pulsed DC vaccine was prepared. Changes in immune cells and cytokines within the tumor microenvironment were measured using flow cytometry and enzyme-linked immunosorbent assay (ELISA). In a lung cancer LLC1 cell tumor-bearing mouse model, treatments included unpulsed DC vaccine, CpG, LLC1-M02-DC, LLC1-M02-WT-DC, and LLC1-M02-DC+CpG. The percentages of CD3⁺CD4⁺ and CD3⁺CD8⁺ T cells, perforin and granzyme expression in CD3⁺ or CD8⁺ T cells in tumor tissues, as well as tumor volume, mouse body weight changes, and survival time were monitored. Results: The percentages of CD3⁺IFN-γ⁺ T cells induced by neoantigens LLC1-M01 and LLC1-M02 were (4.80±1.00)% and (13.81±3.00)%, respectively, which were higher than that induced by the irrelevant peptide VSV-NP43-69 [(1.00±0.30)%; both P＜0.001]. The IFN-γ secretion capacity of effector splenocytes induced by LLC1-M01 was (200.00±45.00) spot-forming units (SFU)/10⁵ cells, showing no significant difference from LLC1-M01-WT [(193.00±42.00) SFU/10⁵ cells; P=0.753]. In contrast, IFN-γ secretion induced by LLC1-M02 was (820.00±200.00) SFU/10⁵ cells, significantly higher than that induced by LLC1-M02-WT [(430.00±100.00) SFU/10⁵ cells; P＜0.001]. At an effector-to-target ratio of 50:1, the specific killing rate of LLC1 cells by effector T cells induced by LLC1-M02-DC was (35.02±8.00)%, which was higher than the rates of killing against MC38 and B16-F10 cells (P＜0.001), and also higher than that induced by M02-WT against LLC1 cells [(20.01±4.00)%; P＜0.001]. Compared with the no-CpG group, the CpG group showed increased percentages of CD3⁺CD8⁺, CD3⁺perforin⁺, CD3⁺granzyme⁺, CD8⁺perforin⁺, and CD8⁺granzyme⁺ T cells in tumor tissue (all P＜0.01), downregulated expression of tumor necrosis factor-alpha (TNF-α), IFN-γ, interleukin (IL)-2, and IL-12 (all P＜0.01), and upregulated expression of IL-10 and IL-13 (all P＜0.01). In tumor-bearing mice treatment experiments, compared with the unpulsed DC vaccine group, CpG group, and LLC1-M02-WT-DC group, tumor growth was significantly inhibited in the LLC1-M02-DC group. The LLC1-M02-DC+CpG group exhibited stronger tumor growth inhibition than the LLC1-M02-DC group (P＜0.001), while no significant differences in body weight were observed among groups. The median survival times of tumor-bearing mice in the unpulsed DC vaccine, CpG, LLC1-M02-DC, LLC1-M02-WT-DC, and LLC1-M02-DC+CpG groups were 28.0, 30.5, 55.0, 37.5, and 79.0 days, respectively. Survival time in the LLC1-M02-DC group was significantly longer than that in the LLC1-M02-WT-DC group (P=0.045) but significantly shorter than that in the LLC1-M02-DC+CpG group (P=0.008). Conclusions: The neoantigen LLC1-M02 from the murine LLC1 cell line exhibits strong immunogenicity. The LLC1-M02-DC vaccine combined with CpG enhances the inhibitory effect on lung "cold" tumors.