Role of additive size in the segmental dynamics and mechanical properties of cross-linked polymers.

Thermoset materials often involve the addition of molecular and nanoparticle additives to alter various chemo-physical properties of importance in their ultimate applications. The resulting compositional heterogeneities can lead to either enhancement or degradation of thermoset properties, depending on the additive chemical structure and concentration. We tentatively explore this complex physical phenomenon through the consideration of a model polymeric additive to our coarse-grained (CG) thermoset investigated in previous works by simply varying the size of additive segments compared to those of polymer melt. We find that the additive modified thermoset material becomes chemically heterogeneous from additive aggregation when the additive segments become much smaller than those of the thermoset molecules, and a clear evidence is observed in the spatial distribution of local molecular stiffness estimated from Debye-Waller factor 〈u2〉. Despite the non-monotonic variation trends observed in dynamical and mechanical properties with decreasing additive segmental size, both the structural relaxation time and moduli (i.e., shear modulus and bulk modulus) exhibit scaling laws with 〈u2〉. The present work highlights the complex role of additive size played in the dynamical and mechanical properties of thermoset polymers, which should provide a better understanding for the glass formation process of cross-linked polymer composites.

Modeling-driven materials by design for conjugated polymers: insights into optoelectronic, conformational, and thermomechanical properties.

Conjugated polymers (CPs) have emerged as pivotal functional materials in the realm of flexible electronics and optoelectronic devices due to their unique blend of mechanical flexibility, solution processability, and tunable optoelectronic properties. This review synthesizes the latest molecular simulation-driven insights obtained from various multiscale modeling techniques, including quantum mechanics (QM), all-atomistic (AA) molecular dynamics (MD), coarse-grained (CG) modeling, and machine learning (ML), to elucidate the optoelectronic, structural, and thermomechanical properties of CPs. By integrating findings from our recent computational work with key experimental studies, we highlight the molecular mechanisms influencing the multifunctional performance of CPs. This comprehensive understanding aims to guide future research directions and applications in the modeling assisted design of high-performance CP-based materials and devices.

Removal of benzo[a]pyrene from the soil by adsorption coupled with degradation on saponin-modified bentonite immobilized crude enzymes.

Bentonite is a non-metallic mineral with montmorillonite as the main component. It is an environmentally friendly mineral material with large reserves, wide distribution, and low price. Bentonite can be easily modified organically using the surfactant saponin to obtain saponin-modified bentonite (Sap-BT). This study investigates the immobilization of crude enzymes obtained from Trametes versicolor by physical adsorption with Sap-BT. Thus, saponin-modified bentonite immobilized crude enzymes (CE-Sap-BT) were developed to remove benzo[a]pyrene. Immobilization improves the stability of free enzymes. CE-Sap-BT can maintain more than 80% of activity at 45 °C and after storage for 15 d. Additionally, CE-Sap-BT exhibited a high removal rate of benzo[a]pyrene in soil, with 65.69% after 7 d in highly contaminated allotment soil and 52.90% after 6 d in actual soil contaminated with a low concentration of benzo[a]pyrene at a very low laccase dosage (0.1 U/3 g soil). The high catalytic and removal performance of CE-Sap-BT in contaminated sites showed more excellent practical application value.

Tumor battlefield within inflamed, excluded or desert immune phenotypes: the mechanisms and strategies.

The tumor microenvironment demonstrates great immunophenotypic heterogeneity, which has been leveraged in traditional immune-hot/cold tumor categorization based on the abundance of intra-tumoral immune cells. By incorporating the spatial immune contexture, the tumor immunophenotype was further elaborated into immune-inflamed, immune-excluded, and immune-desert. However, the mechanisms underlying these different immune phenotypes are yet to be comprehensively elucidated. In this review, we discuss how tumor cells and the tumor microenvironment interact collectively to shape the immune landscape from the perspectives of tumor cells, immune cells, the extracellular matrix, and cancer metabolism, and we summarize potential therapeutic options according to distinct immunophenotypes for personalized precision medicine.

Deep learning-based detection and semi-quantitative model for spread through air spaces (STAS) in lung adenocarcinoma.

Tumor spread through air spaces (STAS) is a distinctive metastatic pattern affecting prognosis in lung adenocarcinoma (LUAD) patients. Several challenges are associated with STAS detection, including misdetection, low interobserver agreement, and lack of quantitative analysis. In this research, a total of 489 digital whole slide images (WSIs) were collected. The deep learning-based STAS detection model, named STASNet, was constructed to calculate semi-quantitative parameters associated with STAS density and distance. STASNet demonstrated an accuracy of 0.93 for STAS detection at the tiles level and had an AUC of 0.72-0.78 for determining the STAS status at the WSI level. Among the semi-quantitative parameters, T10S, combined with the spatial location information, significantly stratified stage I LUAD patients on disease-free survival. Additionally, STASNet was deployed into a real-time pathological diagnostic environment, which boosted the STAS detection rate and led to the identification of three easily misidentified types of occult STAS.

Inter-Oligomer Interaction Influence on Photoluminescence in Cis-Polyacetylene Semiconductor Materials.

Semiconducting conjugated polymers (CPs) are pivotal in advancing organic electronics, offering tunable properties for solar cells and field-effect transistors. Here, we carry out first-principle calculations to study individual cis-polyacetylene (cis-PA) oligomers and their ensembles. The ground electronic structures are obtained using density functional theory (DFT), and excited state dynamics are explored by computing nonadiabatic couplings (NACs) between electronic and nuclear degrees of freedom. We compute the nonradiative relaxation of charge carriers and photoluminescence (PL) using the Redfield theory. Our findings show that electrons relax faster than holes. The ensemble of oligomers shows faster relaxation compared to the single oligomer. The calculated PL spectra show features from both interband and intraband transitions. The ensemble shows broader line widths, redshift of transition energies, and lower intensities compared to the single oligomer. This comparative study suggests that the dispersion forces and orbital hybridizations between chains are the leading contributors to the variation in PL. It provides insights into the fundamental behaviors of CPs and the molecular-level understanding for the design of more efficient optoelectronic devices.

A pro-metastatic tRNA fragment drives aldolase A oligomerization to enhance aerobic glycolysis in lung adenocarcinoma.

Despite being the leading cause of lung cancer-related deaths, the underlying molecular mechanisms driving metastasis progression are still not fully understood. Transfer RNA-derived fragments (tRFs) have been implicated in various biological processes in cancer. However, the role of tRFs in lung adenocarcinoma (LUAD) remains unclear. Our study identified a tRF, tRF-Val-CAC-024, associated with the high-risk component of LUAD, through validation using 3 cohorts. Our findings demonstrated that tRF-Val-CAC-024 acts as an oncogene in LUAD. Mechanistically, tRF-Val-CAC-024 was revealed to bind to aldolase A (ALDOA) dependent on Q125/E224 and promote the oligomerization of ALDOA, resulting in increased enzyme activity and enhanced aerobic glycolysis in LUAD cells. Additionally, we provide preliminary evidence of its potential clinical value by investigating the therapeutic effects of tRF-Val-CAC-024 antagomir-loaded lipid nanoparticles (LNPs) in cell-line-derived xenograft models. These results could enhance our understanding of the regulatory mechanisms of tRFs in LUAD and provide a potential therapeutic target.

A Molecular Dynamics Study of Mechanical and Conformational Properties of Conjugated Polymer Thin Films.

Understanding and predicting the mechanical and conformational properties of conjugated polymer (CP) thin films are a central focus in flexible electronic device research. Employing molecular dynamics simulations with an architecture-transferable chemistry-specific coarse-grained (CG) model of poly(3-alkylthiophene)s (P3ATs), developed by using an energy renormalization approach, we investigate the mechanical and conformational behavior of P3AT thin films during deformation. The density profiles and measures of local mobility identify a softer interfacial layer for all films, the thickness of which does not depend on M w or side-chain length. Remarkably, Young's modulus measured via nanoindentation is more sensitive to M w than for tensile tests, which we attribute to distinct deformation mechanisms. High-M w thin films show increased toughness, whereas longer side-chain lengths of P3AT resulted in lower Young's modulus. Fractures in low-M w thin films occur through chain pullout due to insufficient chain entanglement and crazing in the plastic region. Importantly, stretching promoted both chain alignment and longer conjugation lengths of P3AT, potentially enhancing its electronic properties. For instance, at room temperature, stretching P3HT thin films to 150% increases the conjugated length of P3HT thin films from 2.7 nm to 4.7 nm, aligning with previous experimental findings and all-atom simulation results. Furthermore, high-M w thin films display elevated friction forces due to the chain accumulation on the indenter, with negligible variations in the friction coefficient across all thin film systems. These findings offer valuable insights that enhance our understanding and guide the rational design of CP thin films in flexible electronics.

Electrochemical Bioconjugation of Tryptophan Residues: A Strategy for Peptide Modification.

Interest in electrocatalytic bioconjugation reactions has surged, particularly for modifying tryptophan and tyrosine residues in proteins. We used a cost-effective graphite felt electrode and low-current methodology to achieve selective bioconjugation of tryptophan with thiophenols, yielding up to 92%. This method exclusively labeled tryptophan residues and incorporated fluorinated tryptophan for NMR analysis. Eight polypeptides, including lanreotide and leuprorelin, were effectively coupled, demonstrating the method's versatility and potential for novel diagnostic and therapeutic agents.

Baicalein inhibits biofilm formation of avian pathogenic Escherichia coli in vitro mainly by affecting adhesion.

Avian pathogenic Escherichia coli (APEC) is a widespread bacterium that causes significant economic losses to the poultry industry. APEC biofilm formation may result in chronic, persistent, and recurrent infections in clinics, making treatment challenging. Baicalein is a natural product that exhibits antimicrobial and antibiofilm activities. This study investigates the inhibitory effect of baicalein on APEC biofilm formation at different stages. The minimum inhibitory concentration (MIC) of baicalein on APEC was determined, and the growth curve of APEC biofilm formation was determined. The effects of baicalein on APEC biofilm adhesion, accumulation, and maturation were observed using optical microscopy, confocal laser scanning microscopy, and scanning electron microscopy. The biofilm inhibition rate of baicalein was calculated at different stages. The MIC of baicalein against APEC was 256 µg/mL. The process of APEC biofilm maturation takes approximately 48 h after incubation, with initial adhesion completed at 12 h, and cell accumulation finished at 24 h. Baicalein had a significant inhibitory effect on APEC biofilm formation at concentrations above 1 µg/mL (p < 0.01). Notably, baicalein had the highest rate of biofilm formation inhibition when added at the adhesion stage. Therefore, it can be concluded that baicalein is a potent inhibitor of APEC biofilm formation in vitro and acts, primarily by inhibiting cell adhesion. These findings suggests that baicalein has a potential application for inhibiting APEC biofilm formation and provides a novel approach for the prevention and control APEC-related diseases.

Integrated proteomic profiling identifies amino acids selectively cytotoxic to pancreatic cancer cells.

Pancreatic adenocarcinoma (PDAC) is one of the most deadly cancers, characterized by extremely limited therapeutic options and a poor prognosis, as it is often diagnosed during late disease stages. Innovative and selective treatments are urgently needed, since current therapies have limited efficacy and significant side effects. Through proteomics analysis of extracellular vesicles, we discovered an imbalanced distribution of amino acids secreted by PDAC tumor cells. Our findings revealed that PDAC cells preferentially excrete proteins with certain preferential amino acids, including isoleucine and histidine, via extracellular vesicles. These amino acids are associated with disease progression and can be targeted to elicit selective toxicity to PDAC tumor cells. Both in vitro and in vivo experiments demonstrated that supplementation with these specific amino acids effectively eradicated PDAC cells. Mechanistically, we also identified XRN1 as a potential target for these amino acids. The high selectivity of this treatment method allows for specific targeting of tumor metabolism with very low toxicity to normal tissues. Furthermore, we found this treatment approach is easy-to-administer and with sustained tumor-killing effects. Together, our findings reveal that exocytosed amino acids may serve as therapeutic targets for designing treatments of intractable PDAC and potentially offer alternative treatments for other types of cancers.

Antihypertensive treatment during pregnancy induces long-term changes in gut microbiota and the behaviors of the attention deficit hyperactivity disorder offspring.

The pathogenesis of attention-deficit/hyperactivity disorder (ADHD) has not been fully elucidated. Gestational hypertension could double the probability of ADHD in the offspring, while the initial bacterial communication between the mother and offspring has been associated with psychiatric disorders. Thus, we hypothesize that antihypertensive treatment during pregnancy may abate the impairments in neurodevelopment of the offspring. To test this hypothesis, we chose Captopril and Labetalol, to apply to pregnant spontaneously hypertensive rat (SHR) dams and examined the outcomes in the male offspring. Our data demonstrated that maternal treatment with Captopril and Labetalol had long-lasting changes in gut microbiota and behavioral alterations, including decreased hyperactivity and increased curiosity, spatial learning and memory in the male offspring. Increased diversity and composition were identified, and some ADHD related bacteria were found to have the same change in the gut microbiota of both the dam and offspring after the treatments. LC-MS/MS and immunohistochemistry assays suggested elevated expression of brain derived neurotrophic factor (BDNF) and dopamine in the prefrontal cortex and striatum of offspring exposed to Captopril/ Labetalol, which may account for the improvement of the offspring's psychiatric functions. Therefore, our results support the beneficial long-term effects of the intervention of gestational hypertension in the prevention of ADHD.

Effect of solvent quality and sidechain architecture on conjugated polymer chain conformation in solution.

Conjugated polymers (CPs) are solution-processible for various electronic applications, where solution aggregation and dynamics could impact the morphology in the solid state. Various solvents and solvent mixtures have been used to dissolve and process CPs, but few studies have quantified the effect of solvent quality on the solution behavior of CPs. Herein, we performed static light scattering and small-angle X-ray scattering combined with molecular dynamics (MD) simulation to investigate CP solution behaviors with solvents of varying quality, including poly(3-alkylthiophene) (P3ATs) with various sidechain lengths from -C4H9 to -C12H25, poly[bis(3-dodecyl-2-thienyl)-2,2'-dithiophene-5,5'-diyl] (PQT-12) and poly[2,5-bis(3-dodecylthiophen-2-yl)thieno[3,2-b]thiophene] (PBTTT-12). We found that chlorobenzene is a better solvent than toluene for various CPs, which was evident from the positive second virial coefficient A2 ranging from 0.3 to 4.7 × 10-3 cm3 mol g-2 towards P3ATs. For P3ATs in non-polar solvents, longer sidechains promote more positive A2, indicating a better polymer-solvent interaction, wherein A2 for toluene increases from -5.9 to 1.4 × 10-3 cm3 mol g-2, and in CB, A2 ranges from 1.0 to 4.7 × 10-3 cm3 mol g-2 when sidechain length increases from -C6H13 to -C12H25. Moreover, PQT-12 and PBTTT-12 have strong aggregation tendencies in all solutions, with an apparent positive A2 (∼0.5 × 10-3 cm3 mol g-2) due to multi-chain aggregates and peculiar chain folding. These solvent-dependent aggregation behaviors can be well correlated to spectroscopy measurement results. Our coarse-grained MD simulation results further suggested that CPs with long, dense, and branched sidechains can achieve enhanced polymer-solvent interaction, and thus enable overall better solution dispersion. This work provides quantitative insights into the solution behavior of conjugated polymers that can guide both the design and process of CPs toward next-generation organic electronics.

tRF-29-79 regulates lung adenocarcinoma progression through mediating glutamine transporter SLC1A5.

In recent decades, considerable evidence has emerged indicating the involvement of tRNA-derived fragments (tRFs) in cancer progression through various mechanisms. However, the biological effects and mechanisms of tRFs in lung adenocarcinoma (LUAD) remain unclear. In this study, we screen out tRF-29-79, a 5'-tRF derived from tRNAGlyGCC, through profiling the tRF expressions in three pairs of LUAD tissues. We show that tRF-29-79 is downregulated in LUAD and downregulation of tRF-29-79 is associated with poorer prognosis. In vivo and in vitro assay reveal that tRF-29-79 inhibits proliferation, migration and invasion of LUAD cells. Mechanistically, we discovered that tRF-29-79 interacts with the RNA-binding protein PTBP1 and facilitates the transportation of PTBP1 from nucleus to cytoplasm, which regulates alternative splicing in the 3' untranslated region (UTR) of SLC1A5 pre-mRNA. Given that SLC1A5 is a core transporter of glutamine, we proved that tRF-29-79 mediate glutamine metabolism of LUAD through affecting the stability of SLC1A5 mRNA, thus exerts its anticancer function. In summary, our findings uncover the novel mechanism that tRF-29-79 participates in glutamine metabolism through interacting with PTBP1 and regulating alternative splicing in the 3' UTR of SLC1A5 pre-mRNA.

Patient self-reported experience and satisfaction with golimumab and etanercept treatments for rheumatic diseases: A cohort study.

Golimumab and etanercept both exhibit good efficacy in treating rheumatic diseases, while the patient self-reported measurement of treatment improvement and injection experience lacks sufficient evidence. Hence, this study aimed to compare the satisfaction with disease improvement and injection experience and the level of injection site reactions (ISRs) between golimumab-treated and etanercept-treated patients with rheumatic diseases. A total of 312 patients with rheumatic diseases were serially enrolled. Among them, 158 patients received golimumab (golimumab group); the other 154 patients were treated with etanercept (etanercept group) according to the actual disease status, physician advice, and patient willingness. Satisfaction with disease improvement was assessed using the 7-point Likert scale; satisfaction with injection experience and level of ISRs were both determined by the 5-point Likert scale. Satisfaction degrees with global injection experience (P = .025), injection device (P = .008), injection frequency (P = .010), and injection convenience (P = .003) were superior in the golimumab group to the etanercept group, while satisfaction degrees with global disease improvement, symptom relief, and speed of action did not vary (all P > .050) between the 2 groups. Discomfort (P = .005), swelling (P < .001), pain (P = .028), and burning (P = .035) levels were lower in the golimumab group than in the etanercept group. In addition, among 56 patients with a history of tumor necrosis factor inhibitor treatment before golimumab, 40 (71.4%) patients preferred golimumab to other tumor necrosis factor inhibitor. After switching to golimumab treatment, the level of ISRs in most patients was reduced or comparable. Golimumab achieves a satisfying injection experience and relieves the level of ISRs over etanercept in patients with rheumatic diseases.

A real-world clinicopathological model for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer.

Purpose: This study aimed to develop and validate a clinicopathological model to predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients and identify key prognostic factors. Methods: This retrospective study analyzed data from 279 breast cancer patients who received NAC at Zhejiang Provincial People's Hospital from 2011 to 2021. Additionally, an external validation dataset, comprising 50 patients from Lanxi People's Hospital and Second Affiliated Hospital, Zhejiang University School of Medicine from 2022 to 2023 was utilized for model verification. A multivariate logistic regression model was established incorporating clinical, ultrasound features, circulating tumor cells (CTCs), and pathology variables at baseline and post-NAC. Model performance for predicting pCR was evaluated. Prognostic factors were identified using survival analysis. Results: In the 279 patients enrolled, a pathologic complete response (pCR) rate of 27.96% (78 out of 279) was achieved. The predictive model incorporated independent predictors such as stromal tumor-infiltrating lymphocyte (sTIL) levels, Ki-67 expression, molecular subtype, and ultrasound echo features. The model demonstrated strong predictive accuracy for pCR (C-statistics/AUC 0.874), especially in human epidermal growth factor receptor 2 (HER2)-enriched (C-statistics/AUC 0.878) and triple-negative (C-statistics/AUC 0.870) subtypes, and the model performed well in external validation data set (C-statistics/AUC 0.836). Incorporating circulating tumor cell (CTC) changes post-NAC and tumor size changes further improved predictive performance (C-statistics/AUC 0.945) in the CTC detection subgroup. Key prognostic factors included tumor size >5cm, lymph node metastasis, sTIL levels, estrogen receptor (ER) status and pCR. Despite varied pCR rates, overall prognosis after standard systemic therapy was consistent across molecular subtypes. Conclusion: The developed predictive model showcases robust performance in forecasting pCR in NAC-treated breast cancer patients, marking a step toward more personalized therapeutic strategies in breast cancer.

Energy renormalization for temperature transferable coarse-graining of silicone polymer.

The bottom-up prediction of thermodynamic and mechanical behaviors of polymeric materials based on molecular dynamics (MD) simulation is of critical importance in polymer physics. Although the atomistically informed coarse-grained (CG) model can access greater spatiotemporal scales and retain essential chemical specificity, the temperature-transferable CG model is still a big challenge and hinders widespread application of this technique. Herein, we use a silicone polymer, i.e., polydimethylsiloxane (PDMS), having an incredibly low chain rigidity as a model system, combined with an energy-renormalization (ER) approach, to systematically develop a temperature-transferable CG model. Specifically, by introducing temperature-dependent ER factors to renormalize the effective distance and cohesive energy parameters, the developed CG model faithfully preserved the dynamics, mechanical and conformational behaviors compared with the target all-atomistic (AA) model from glassy to melt regimes, which was further validated by experimental data. With the developed CG model featuring tremendously improved computational efficiency, we systematically explored the influences of cohesive interaction strength and temperature on the dynamical heterogeneity and mechanical response of polymers, where we observed consistent trends with other linear polymers with varying chain rigidity and monomeric structures. This study serves as an extension of our proposed ER approach of developing temperature transferable CG models with diverse segmental structures, highlighting the critical role of cohesive interaction strength on CG modeling of polymer dynamics and thermomechanical behaviors.

Neoadjuvant chemotherapy-induced remodeling of human hormonal receptor-positive breast cancer revealed by single-cell RNA sequencing.

Hormone receptor-positive breast cancer (HR+ BC) is known to be relatively insensitive to chemotherapy, and since chemotherapy has remained the major neoadjuvant therapy for HR+ BC, the undetermined mechanism of chemoresistance and how chemotherapy reshapes the immune microenvironment need to be explored by high-throughput technology. By using single-cell RNA sequencing and multiplexed immunofluorescence staining analysis of HR+ BC samples (paired pre- and post-neoadjuvant chemotherapy (NAC)), the levels of previously unrecognized immune cell subsets, including CD8+ T cells with pronounced expression of T-cell development (LMNA) and cytotoxicity (FGFBP2) markers, CD4+ T cells characterized by proliferation marker (ATP1B3) expression and macrophages characterized by CD52 expression, were found to be increased post-NAC, which were predictive of chemosensitivity and their antitumor function was also validated with in vitro experiments. In terms of immune checkpoint expression of CD8+ T cells, we found their changes were inconsistent post-NAC, that LAG3, VSIR were decreased, and PDCD1, HAVCR2, CTLA4, KLRC1 and BTLA were increased. In addition, we have identified novel genomic and transcriptional patterns of chemoresistant cancer cells, both innate and acquired, and have confirmed their prognostic value with TCGA cohorts. By shedding light on the ecosystem of HR+ BC reshaped by chemotherapy, our results uncover valuable candidates for predicting chemosensitivity and overcoming chemoresistance in HR+ BC.

Integrated transcriptomics, proteomics, and functional analysis to characterize the tissue-specific small extracellular vesicle network of breast cancer.

Small extracellular vesicles (sEVs) are essential mediators of intercellular communication within the tumor microenvironment (TME). Although the biological features of sEVs have been characterized based on in vitro culture models, recent evidence indicates significant differences between sEVs derived from tissue and those derived from in vitro models in terms of both content and biological function. However, comprehensive comparisons and functional analyses are still limited. Here, we collected sEVs from breast cancer tissues (T-sEVs), paired normal tissues (N-sEVs), corresponding plasma (B-sEVs), and tumor organoids (O-sEVs) to characterize their transcriptomic and proteomic profiles. We identified the actual cancer-specific sEV signatures characterized by enriched cell adhesion and immunomodulatory molecules. Furthermore, we revealed the significant contribution of cancer-associated fibroblasts in the sEV network within the TME. In vitro model-derived sEVs did not entirely inherit the extracellular matrix- and immunity regulation-related features of T-sEVs. Also, we demonstrated the greater immunostimulatory ability of T-sEVs on macrophages and CD8+ T cells compared to O-sEVs. Moreover, certain sEV biomarkers derived from noncancer cells in the circulation exhibited promising diagnostic potential. This study provides valuable insights into the functional characteristics of tumor tissue-derived sEVs, highlighting their potential as diagnostic markers and therapeutic agents for breast cancer.

Competing Effects of Molecular Additives and Cross-Link Density on the Segmental Dynamics and Mechanical Properties of Cross-Linked Polymers.

The introduction of molecular additives into thermosets often results in changes in their dynamics and mechanical properties that can have significant ramifications for diverse applications of this broad class of materials such as coatings, high-performance composites, etc. Currently, there is limited fundamental understanding of how such additives influence glass formation in these materials, a problem of broader significance in glass-forming materials. To address this fundamental problem, here, we employ a simplified coarse-grained (CG) model of a polymer network as a model of thermoset materials and then introduce a polymer additive having the same inherent rigidity and polymer-polymer interaction strength as the cross-linked polymer matrix. This energetically "neutral" or "self-plasticizing" additive model gives rise to non-trivial changes in the dynamics of glass formation and provides an important theoretical reference point for the technologically more important case of interacting additives. Based on this rather idealized model, we systematically explore the combined effect of varying the additive mass percentage (m) and cross-link density (c) on the segmental relaxation dynamics and mechanical properties of a model thermoset material with additives. We find that increasing the additive mass percentage m progressively decreases both the glass-transition temperature Tg and the fragility of glass formation, a trend opposite to increasing c so that these thermoset variables clearly have a competing effect on glass formation in these model materials. Moreover, basic mechanical properties (i.e., bulk, shear, and tensile moduli) likewise exhibit a competitive variation with the increase of m and c, which are strongly correlated with the Debye-Waller parameter ⟨u2⟩, a measure of material stiffness at a molecular scale. Our findings prove beneficial in the development of structure-property relationships for the cross-linked polymers, which could help guide the design of such network materials with tailored physical properties.