Feature fusion method for pulmonary tuberculosis patient detection based on cough sound.

Since the COVID-19, cough sounds have been widely used for screening purposes. Intelligent analysis techniques have proven to be effective in detecting respiratory diseases. In 2021, there were up to 10 million TB-infected patients worldwide, with an annual growth rate of 4.5%. Most of the patients were from economically underdeveloped regions and countries. The PPD test, a common screening method in the community, has a sensitivity of as low as 77%. Although IGRA and Xpert MTB/RIF offer high specificity and sensitivity, their cost makes them less accessible. In this study, we proposed a feature fusion model-based cough sound classification method for primary TB screening in communities. Data were collected from hospitals using smart phones, including 230 cough sounds from 70 patients with TB and 226 cough sounds from 74 healthy subjects. We employed Bi-LSTM and Bi-GRU recurrent neural networks to analyze five traditional feature sets including the Mel frequency cepstrum coefficient (MFCC), zero-crossing rate (ZCR), short-time energy, root mean square, and chroma_cens. The incorporation of features extracted from the speech spectrogram by 2D convolution training into the Bi-LSTM model enhanced the classification results. With traditional futures, the best TB patient detection result was achieved with the Bi-LSTM model, with 93.99% accuracy, 93.93% specificity, and 92.39% sensitivity. When combined with a speech spectrogram, the classification results showed 96.33% accuracy, 94.99% specificity, and 98.13% sensitivity. Our findings underscore that traditional features and deep features have good complementarity when fused using Bi LSTM modelling, which outperforms existing PPD detection methods in terms of both efficiency and accuracy.

A comprehensive study of the colloidal properties, biocompatibility, and synergistic antioxidant actions of Antarctic krill phospholipids.

Excipient selection is crucial to address the oxidation and solubility challenges of bioactive substances, impacting their safety and efficacy. AKPL, a novel ω-3 polyunsaturated fatty acids (PUFAs) esterified phospholipid derived from Antarctic krill, demonstrates unique antioxidant capabilities and synergistic effects. It exhibits pronounced surface activity and electronegativity at physiological pH, as evidenced by a critical micelle concentration (CMC) of 0.15 g/L and ζ-potential of -49.9 mV. In aqueous environments, AKPL self-assembles into liposomal structures, offering high biocompatibility and promoting cell proliferation. Its polyunsaturated bond-rich structure provides additional oxidation sites, imparting antioxidant properties superior to other phospholipids like DSPC and DOPC. Additionally, AKPL augments the efficacy of lipophilic antioxidants, such as alpha-tocopherol and curcumin, in aqueous media through both intermolecular and intramolecular interactions. In sum, AKPL emerges as an innovative unsaturated phospholipid, offering new strategies for encapsulating and delivering oxygen-sensitive agents.

A potential virulence factor: Brucella flagellin FliK does not affect the main biological properties but inhibits the inflammatory response in RAW264.7 cells.

The bacterial flagellum is an elongated filament that protrudes from the cell and is responsible for bacterial motility. It can also be a pathogen-associated molecular pattern (PAMP) that regulates the host immune response and is involved in bacterial pathogenicity. In contrast to motile bacteria, the Brucella flagellum does not serve a motile purpose. Instead, it plays a role in regulating Brucella virulence and the host's immune response, similar to other non-motile bacteria. The flagellin protein, FliK, plays a key role in assembly of the flagellum and also as a potential virulence factor involved in the regulation of bacterial virulence and pathogenicity. In this study, we generated a Brucella suis S2 flik gene deletion strain and its complemented strain and found that deletion of the flik gene has no significant effect on the main biological properties of Brucella, but significantly enhanced the inflammatory response induced by Brucella infection of RAW264.7 macrophages. Further experiments demonstrated that the FliK protein was able to inhibit LPS-induced cellular inflammatory responses by down-regulating the expression of MyD88 and NF-κB, and by decreasing p65 phosphorylation in the NF-κB pathway; it also inhibited the expression of NLRP3 and caspase-1 in the NLRP3 inflammasome pathway. In conclusion, our study suggests that Brucella FliK may act as a virulence factor involved in the regulation of Brucella pathogenicity and modulation of the host immune response.

Hospice Knowledge, Attitudes, and Preference among Older Chinese Immigrants in the United States.

Racial disparities in hospice use are a longstanding concern in the U.S. Asian Americans are among the least likely to receive hospice care and to be included in studies on this topic. This study examined the knowledge, attitudes, and preferences related to hospice care among older Chinese immigrants and associated factors. A sample of 262 Chinese immigrants age 60+ was recruited from six older adult centers in NYC. In-person interviews were conducted in Mandarin and Cantonese. Non-English-speaking older Chinese immigrants had very limited knowledge about hospice care. Only 26% of respondents had heard of hospice, and a few could correctly define any components. After receiving a comprehensive definition of hospice care, study participants expressed a positive attitude and a strong willingness to use hospice if near the end of life. Notably, some respondents still held misconceptions about hospice and were less positive in their attitude and preference for hospice care. These findings underscore the necessity for clear and accessible information about hospice among this population throughout the trajectory from good health to end of life. Further research is needed to identify the range of factors that influence the attitudes and preferences of older Chinese immigrants toward hospice care.

Mg-MOF-74 Derived Defective Framework for Hydrogen Storage at Above-Ambient Temperature Assisted by Pt Catalyst.

Metal-organic frameworks (MOFs) are promising candidates for room-temperature hydrogen storage materials after modification, thanks to their ability to chemisorb hydrogen. However, the hydrogen adsorption strength of these modified MOFs remains insufficient to meet the capacity and safety requirements of hydrogen storage systems. To address this challenge, a highly defective framework material known as de-MgMOF is prepared by gently annealing Mg-MOF-74. This material retains some of the crystal properties of the original Mg-MOF-74 and exhibits exceptional hydrogen storage capacity at above-ambient temperatures. The MgO5 knots around linker vacancies in de-MgMOF can adsorb a significant amount of dissociated and nondissociated hydrogen, with adsorption enthalpies ranging from -22.7 to -43.6 kJ mol-1, indicating a strong chemisorption interaction. By leveraging a spillover catalyst of Pt, the material achieves a reversible hydrogen storage capacity of 2.55 wt.% at 160 °C and 81 bar. Additionally, this material offers rapid hydrogen uptake/release, stable cycling, and convenient storage capabilities. A comprehensive techno-economic analysis demonstrates that this material outperforms many other hydrogen storage materials at the system level for on-board applications.

Aerobic Oxidative Carboxylation of Styrene Over Cobalt Catalysts: Integrated CO2 Capture and Conversion.

The direct synthesis of cyclic carbonates through oxidative carboxylation of alkenes using CO2 and O2 offers a sustainable and carbon-neutral method for CO2 utilization, which is, however, still a largely unexplored field. Here we develop a single-atom catalyst (SAC) Co-N/O-C as the earth-abundant metal catalyst for the oxidative carboxylation of styrene with CO2 and O2. Remarkably, even using the flue gas as an impure CO2 and O2 source, desired cyclic carbonate could be obtained with moderate productivity, which shows the potential for integrated CO2 capture and conversion, leveraging the high CO2 adsorption capacity of Co-N/O-C. In addition, the catalyst can be reused five times without an obvious decline in activity. Detailed characterizations and theoretical calculations elucidate the crucial role of single Co atoms in activating O2 and CO2, as well as controlling selectivity.

Underwater dynamic polarization imaging without dependence on the background region.

Active-polarization imaging holds significant promise for achieving clear underwater vision. However, only static targets were considered in previous studies, and a background region was required for image restoration. To address these issues, this study proposes an underwater dynamic polarization imaging method based on image pyramid decomposition and reconstruction. During the decomposition process, the polarized image is downsampled to generate an image pyramid. Subsequently, the spatial distribution of the polarization characteristics of the backscattered light is reconstructed by upsampling, which recovered the clear scene. The proposed method avoids dependence on the background region and is suitable for moving targets with varying polarization properties. The experimental results demonstrate effective elimination of backscattered light while sufficiently preserving the target details. In particular, for dynamic targets, processing times that fulfill practical requirements and yield superior recovery effects are simultaneously obtained.

Synergistic Protecting-Etching Synthesis of Carbon Nanoboxes@Silicon for High-Capacity Lithium-Ion Battery.

Silicon (Si) is considered as the most likely choice for the high-capacity lithium-ion batteries owing to its ultrahigh theoretical capacity (4200 mA h g-1) being over 10 times than that of traditional graphite anode materials (372 mA h g-1). However, its widespread application is limited by problems such as a large volume expansion and low electrical conductivity. Herein, we design a hollow nitrogen-doped carbon-coated silicon (Si@Co-HNC) composite in a water-based system via a synergistic protecting-etching strategy of tannic acid. The prepared Si@Co-HNC composite can effectively mitigate the volume change of silicon and improve the electrical conductivity. Moreover, the abundant voids inside the carbon layer and the porous carbon layer accelerate the transport of electrons and lithium ions, resulting in excellent electrochemical performance. The reversible discharge capacity of 1205 mA h g-1 can be retained after 120 cycles at a current density of 0.5 A g-1. In particular, the discharge capacity can be maintained at 1066 mA h g-1 after 300 cycles at a high current density of 1 A g-1. This study provides a new strategy for the design of Si-based anode materials with excellent electrical conductivity and structural stability.

TRAIL predisposes non-small cell lung cancer to ferroptosis by regulating ASK-1/JNK1 pathway.

OBJECTIVE: Our current study aimed to assess the relationship between TNF-related apoptosis-inducing ligand (TRAIL) and ferroptosis in non-small cell lung cancer (NSCLC) development. METHODS: The expression of TRAIL was detected by western blot, RT-qRCR and immunohistochemistry. The viability of NSCLC cells was analyzed by CCK-8 kit. The migration and invasion of NSCLC cells were detected by wound healing assay and transwell assay, respectively. Labile iron pool (LIP) was detected based on the calcein-acetoxymethyl ester method. Ferrous iron (Fe2+) and iron levels were assessed by detection kits. The levels of superoxide dismutase (SOD), catalase (CAT), and malondialdehyde (MDA) were measured using corresponding detection kits. Mice tumor xenograft models were used for the in vivo research. RESULTS: The expression of TRAIL was reduced in H1299, NCL-H1395, and A549 cells compared with BEAS-2B cells. The up-regulation of TRAIL expression significantly reduced cell viability, invasion, and migration of H1299 and A549 cells. TRAIL reduced the expression of ferroptosis-related genes (FTH1, GPX4, and SLC7A11), increased the levels of LIP, iron, and Fe2+, and promoted lipid peroxidation, thereby predisposing NSCLC cells to ferroptosis. TRAIL up-regulated the expression of phosphate modification of ASK-1 and JNK. ASKI-1 inhibitor GS-4977 attenuated the effects of TRAIL on the viability, migration, invasion, and ferroptosis of H1299 cells. Furthermore, TRAIL further suppressed tumor growth and ferroptosis in mice tumor xenograft models. CONCLUSION: We indicated that overexpression of TRAIL induced ferroptosis in NSCLC cells and exerted anti-tumor effects. Mechanistically, TRAIL promoted ferroptosis by the activation of the ASK-1/JNK1 pathway. Our results may provide new therapeutic strategies for NSCLC.

Efficient Alkene Hydroformylation by Co-C Symmetry-Breaking Sites.

Alkene hydroformylation is one of the largest industrial reactions on an industrial scale; however, the development of nonnoble heterogeneous catalysts is usually limited by their low activities and stabilities. Herein, we constructed a 1% Co2C/SiO2 catalyst featuring Co-Cvacancy-Co-C symmetry-breaking sites, which generated a polar surface exhibiting a moderate charge density gradient at the localized Co atoms. Comparatively, this catalyst exhibited notable enhancements in the adsorption and activation of the reactants, as well as in the polarity between intermediates. Significantly, the spatial distance between the adsorption sites of intermediates was reduced, thereby effectively decreasing the energy barrier of reaction processes. As the density of the symmetry-breaking sites increased, the turnover number for propene hydroformylation soared to 18 363, exceeding the activity of heterogeneous Co-based catalysts reported thus far by 1 or 2 orders of magnitude, and the catalyst exhibited high stability during the reaction. This study provides a methodology for constructing atomically active sites, which holds great potential for the design and development of highly efficient catalysts.

[Contamination levels of perfluorinated and polyfluoroalkyl compounds in breast milk and assessment of their exposure risk to infants].

The purposes of this study are to explore the contamination levels of perfluorinated and polyfluoroalkyl substances (PFASs) in breast milk and assess their exposure risk to infants. Based on data from a birth cohort study conducted in Yingcheng, Hubei Province, from 2018 to 2021, the contents of 23 types of PFASs in the breast milk of 324 pregnant women were determined using isotope dilution-high performance liquid chromatography-tandem mass spectrometry. Multiple linear regression was then performed to analyze the effects of various demographic characteristics and eating habits on the concentration of PFASs in breast milk. The daily PFASs intake of infants through breast milk was estimated, and the exposure risk of infants was also assessed. The results revealed that 23 types of PFASs in breast milk had good linear relationships in the range of 0.2-100 ng/mL, with correlation coefficients greater than 0.992. The limits of detection were 5-42 pg/mL, the limits of quantification were 15-126 pg/mL, the recoveries were 65.6%-108.1%, and the relative standard deviations were 1.6%-12.8%. Perfluorooctane sulfonic acid (PFOS), perfluorooctanoate acid (PFOA), and perfluorohexanesulfonic acid (PFHxS), with median concentrations of 200.7, 63.5, and 25.2 pg/mL, respectively, were the main PFASs found in breast milk. The detection rates of these three contaminants were higher than 80%, whereas the detection rates of other compounds were lower than 45%. The results of multiple linear regression showed that older pregnant women and a higher frequency of pickled food intake may be related to increased PFAS levels in breast milk whereas a higher frequency of legume intake may be related to decreased PFAS levels in breast milk. The median estimated daily intakes (EDIs) of PFOS, PFOA, and PFHxS for infants were 25.1, 7.9, and 3.2 ng/(kg·d), respectively. In summary, this study found notable PFAS levels in breast milk in Yingcheng, Hubei Province. Among these PFASs, PFOS, PFOA, and PFHxS were the main contaminants. Maternal age as well as pickled food and legume intake may affect the PFAS level in breast milk. The health risk of PFAS intake through breast milk to some infants is worthy of attention and further study.

Toxicity and oxidative stress of HepG2 and HL-7702 cells induced by PAH4 using oil as a carrier.

Polycyclic aromatic hydrocarbons (PAHs), a widespread class of food pollutants, are commonly exposed to humans along with edible oil. The dietary exposure pattern of PAH4 was simulated to study the toxicity and oxidative stress of oil-based PAH4 on hepatocytes. The findings demonstrated that oil-based PAH4 induced cell viability and mitochondrial membrane potential decreased and promoted apoptosis and oxidative stress in a concentration-dependent manner. Benzo[a]pyrene had the strongest toxicity and HL-7702 cells were more sensitive to toxicity than HepG2 cells, due to differences in induced CYP1A enzyme activity. Oil-based PAH4 had greater cytotoxicity than PAH4, attributed to the synergistic effect of oil and PAH4. Furthermore, oil-based PAH4 induced oxidative stress in HepG2 and HL-7702 cells through the same AHR-Nrf2-KEAP1 pathway, which was elucidated by detecting genes and proteins expression. This study lays the foundation for elucidating the harm of dietary exposure to PAHs and reminds us that food composition may increase the harm of PAHs.

Proteomic Analysis of Staphylococcus aureus Treated with ShangKeHuangShui.

Staphylococcus aureus (SAU) stands as the prevailing pathogen in post-traumatic infections, with the emergence of antibiotic resistance presenting formidable treatment hurdles. The pressing need is to explore novel antibiotics to address this challenge. ShangKeHuangShui (SKHS), a patented traditional Chinese herbal formula, has gained widespread use in averting post-traumatic infections, but its biological effects remain incomplete understanding. This study's primary objective was to delve into the antibacterial properties, potential antibacterial compounds within SKHS, and their associated molecular targets. In vitro SKHS antibacterial assays demonstrated that the minimum inhibitory concentration (MIC) was 8.625 mg/mL and the minimum bactericide concentration (MBC) was 17.25 mg/mL. Proteomic analysis based on tandem mass tag (TMT) showed significant changes in the expression level of 246 proteins in SKHS treated group compared to control group, with 79 proteins upregulated and 167 proteins downregulated (>1.5-fold, p < 0.05). Subsequently, thirteen target proteins related to various biological processes and multiple metabolic pathways were selected to conduct parallel reaction monitoring (PRM) and molecular docking screen. In protein tyrosine phosphatase PtpA (ptpA) docking screening, phellodendrine and obacunone can bind to ptpA with the binding energy of - 8.4 and - 8.3 kcal/mol, respectively. This suggests their potential impact on antibacterial activity by modulating the two-component system of SAU. The discovery lays a groundwork for future research endeavors for exploring new antibacterial candidates and elucidating specific active chemical components within SKHS that match target proteins. Further investigations are imperative to unveil the biological effects of these monomers and their potential synergistic actions.

Comparison of risk prediction models for the progression of pelvic inflammatory disease patients to sepsis: Cox regression model and machine learning model.

Introduction: The present study presents the development and validation of a clinical prediction model using random survival forest (RSF) and stepwise Cox regression, aiming to predict the probability of pelvic inflammatory disease (PID) progressing to sepsis. Methods: A retrospective cohort study was conducted, gathering clinical data of patients diagnosed with PID between 2008 and 2019 from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Patients who met the Sepsis 3.0 diagnostic criteria were selected, with sepsis as the outcome. Univariate Cox regression and stepwise Cox regression were used to screen variables for constructing a nomogram. Moreover, an RSF model was created using machine learning algorithms. To verify the model's performance, a calibration curve, decision curve analysis (DCA), and receiver operating characteristic (ROC) curve were utilized. Furthermore, the capabilities of the two models for estimating the incidence of sepsis in PID patients within 3 and 7 days were compared. Results: A total of 1064 PID patients were included, of whom 54 had progressed to sepsis. The established nomogram highlighted dialysis, reduced platelet (PLT) counts, history of pneumonia, medication of glucocorticoids, and increased leukocyte counts as significant predictive factors. The areas under the curve (AUCs) of the nomogram for prediction of PID progression to sepsis at 3-day and 7-day (3-/7-day) in the training set and the validation set were 0.886/0.863 and 0.824/0.726, respectively, and the C-index of the model was 0.8905. The RSF displayed excellent performance, with AUCs of 0.939/0.919 and 0.712/0.571 for 3-/7-day risk prediction in the training set and validation set, respectively. Conclusion: The nomogram accurately predicted the incidence of sepsis in PID patients, and relevant risk factors were identified. While the RSF model outperformed the Cox regression models in predicting sepsis incidence, its performance exhibited some instability. On the other hand, the Cox regression-based nomogram displayed stable performance and improved interpretability, thereby supporting clinical decision-making in PID treatment.

Predictive Value of Machine Learning for Platinum Chemotherapy Responses in Ovarian Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: Machine learning is a potentially effective method for predicting the response to platinum-based treatment for ovarian cancer. However, the predictive performance of various machine learning methods and variables is still a matter of controversy and debate. OBJECTIVE: This study aims to systematically review relevant literature on the predictive value of machine learning for platinum-based chemotherapy responses in patients with ovarian cancer. METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we systematically searched the PubMed, Embase, Web of Science, and Cochrane databases for relevant studies on predictive models for platinum-based therapies for the treatment of ovarian cancer published before April 26, 2023. The Prediction Model Risk of Bias Assessment tool was used to evaluate the risk of bias in the included articles. Concordance index (C-index), sensitivity, and specificity were used to evaluate the performance of the prediction models to investigate the predictive value of machine learning for platinum chemotherapy responses in patients with ovarian cancer. RESULTS: A total of 1749 articles were examined, and 19 of them involving 39 models were eligible for this study. The most commonly used modeling methods were logistic regression (16/39, 41%), Extreme Gradient Boosting (4/39, 10%), and support vector machine (4/39, 10%). The training cohort reported C-index in 39 predictive models, with a pooled value of 0.806; the validation cohort reported C-index in 12 predictive models, with a pooled value of 0.831. Support vector machine performed well in both the training and validation cohorts, with a C-index of 0.942 and 0.879, respectively. The pooled sensitivity was 0.890, and the pooled specificity was 0.790 in the training cohort. CONCLUSIONS: Machine learning can effectively predict how patients with ovarian cancer respond to platinum-based chemotherapy and may provide a reference for the development or updating of subsequent scoring systems.

Revealing Distance-Dependent Synergy between MnCo2O4 and Co-N-C in Boosting the Oxygen Reduction Reaction.

Synergistic effects have been applied to a variety of hybrid electrocatalysts to improve their activity and selectivity. Understanding the synergistic mechanism is crucial for the rational design of these types of catalysts. Here, we synthesize a MnCo2O4/Co-N-C hybrid electrocatalyst for the oxygen reduction reaction (ORR) and systematically investigate the synergy between MnCo2O4 nanoparticles and Co-N-C support. Theoretical simulations reveal that the synergy is closely related to the distance between active sites. For a pair of remote active sites, the ORR proceeds through the known 2e- + 2e- relay catalysis while the direct 4e- ORR occurs on a pair of adjacent active sites. Therefore, the formation of the undesired byproduct (H2O2) is inhibited at the interface region between MnCo2O4 and Co-N-C. This synergistic effect is further verified on an anion-exchange membrane fuel cell. The findings deepen the understanding of synergistic catalysis and will provide guidance for the rational design of hybrid electrocatalysts.

Simultaneously Enhanced Thermoelectric and Mechanical Performance in SnSe-Based Nanocomposites Produced via Sintering SnSe and KCu7S4 Nanomaterials.

Both thermoelectric and mechanical properties are important to the practical applications of thermoelectric materials. Herein, we develop a strategy for alloying KCu7S4 to improve the dimensionless figure of merit (zT), compressive strength, and Vickers hardness of polycrystalline SnSe. Through chemical synthesis and particle mixing in solutions, powders with SnSe nanoparticles and KCu7S4 nanowires are produced, and the subsequent spark plasma sintering triggers the reaction between the two chalcogenides, resulting in the formation of Cu2SnSe3 nanoparticles and substitution of Cu and S in the SnSe matrix. The composition tuning and secondary phase formation effectively enhance the power factor and diminish the lattice thermal conductivity, leading to a maximum zT of 1.13 at 823 K for the optimal sample, which is improved by 135% over that of SnSe. Simultaneously, the compressive strength and hardness are also enhanced, as exemplified by a high compressive strength of 135 MPa that is enhanced by ∼81% compared to that of SnSe. The current study demonstrates effective composite and composition design toward enhanced thermoelectric and mechanical performance in polycrystalline SnSe.

Exposure, bioaccumulation, and risk assessment of organophosphate flame retardants in crayfish in the middle and lower reaches of the Yangtze River.

Organophosphate flame retardants (OPFRs), a novel class of persistent pollutants, are widely distributed in the environment, and their potential health risks have garnered significant global attention in recent years. Crayfish is a popular freshwater crustacean product in China primarily sourced from the middle and lower reaches of the Yangtze River. The purpose of this study was to investigate the exposure levels of OPFRs in crayfish, assess the health and safety risks associated with crayfish consumption, and explore the bioaccumulation of OPFRs in environmental water and sediment on crayfish. Ultra-high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) was employed to analyze 7 common OPFRs in 106 crayfish samples and 76 environmental samples. The results revealed that OPFRs were detected at a high frequency of 100 % in crayfish, with tripropyl phosphate (TPP) being the predominant pollutant found in edible portions while also exhibiting secondary contamination within the crayfish food chain. Monte Carlo modeling combined with @risk risk assessment software demonstrated that TPP present in crayfish muscles had the most substantial impact on health effects, however, overall OPFR exposure did not pose significant risks to human health. Furthermore, analysis of OPFRs bioenrichment ability indicated that crayfish predominantly accumulated these compounds within their edible parts from surrounding environmental water sources, particularly highlighting TPP's potential for bioaccumulation.

Combined toxicity of oil-based PAH4 mixtures on HL-7702 cells.

Polycyclic aromatic hydrocarbons (PAHs) as a group of prevalent persistent organic pollutants in the environment are always found as mixtures. The combined toxicity of oil-based PAH4 seems seldom to be mentioned. To evaluate the combined toxicity of oil-based PAH4 mixtures on HL-7702 cells, the effects of single, binary, ternary, and quaternary mixtures on cell viability were examined, and the concentration addition model and combination index (CI)-isobologram model were selected to predict the toxicological interactions of the mixtures. The results showed that the PAH4 mixtures had a concentration-dependent effect on cell viability. The CI model was more suitable for elucidating the toxicity interactions of mixtures. In addition, the combined toxicity of BaA + BaP and BaA + Chr + BbF + BaP was antagonistic, BaA + Chr, BaA + BbF, Chr + BbF, and BaA + Chr + BbF was synergistic, and the remaining mixtures shifted from antagonistic to synergistic. Antagonistic effects were observed in all mixtures containing BaP, indicating that oil-based PAH4 mixtures containing BaP had a mitigating effect on cytotoxicity. Furthermore, BbF was identified as playing a key role in the synergistic effects in binary and ternary mixtures. This study provided a new acknowledgment to assess the interactions of PAH4 mixtures which is helpful for further study of the toxicity risks in the environment.