COVID-19 acts like a stress test, uncovering the vulnerable part of the human body: a retrospective study of 1640 cases in China

BACKGROUND

Since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection exhibits multi-organ damage with diverse complications, the correlation between age, gender, medical history and clinical manifestations of novel coronavirus disease 2019 (COVID-19) patients was investigated.

METHODS

1640 patients who were infected with SARS-CoV-2 and hospitalized at the First Affiliated Hospital of Ningbo University from 22 December 2022 to 1 March 2023 were categorized and analysed. Normal distribution test and variance homogeneity test were performed. Based on the test results, one-way analysis of variance, Pearson's chi-squared test and logistic regression analysis were conducted in the study.

RESULTS

According to the ANOVA, there was a significant difference in the age distribution (P = .001) between different clinical presentations, while gender did not (P = .06). And regression analysis showed that age, hypertension, atherosclerosis and cancer were significant hazard factors for the development of predominant clinical manifestations in patients hospitalized with novel COVID-19. Additionally, infection with SARS-CoV-2 has the potential to exacerbate the burden on specific diseased or related organs.

CONCLUSION

The elderly who are infected with SARS-CoV-2 ought to be treated with emphasis not only on antiviral therapy but also on individualized treatment that takes their medical history and comorbidities into account.

Elimination of Pathogen Biofilms via Postbiotics from Lactic Acid Bacteria: A Promising Method in Food and Biomedicine

Pathogenic biofilms provide a naturally favorable barrier for microbial growth and are closely related to the virulence of pathogens. Postbiotics from lactic acid bacteria (LAB) are secondary metabolites and cellular components obtained by inactivation of fermentation broth; they have a certain inhibitory effect on all stages of pathogen biofilms. Postbiotics from LAB have drawn attention because of their high stability, safety dose parameters, and long storage period, which give them a broad application prospect in the fields of food and medicine. The mechanisms of eliminating pathogen biofilms via postbiotics from LAB mainly affect the surface adhesion, self-aggregation, virulence, and QS of pathogens influencing interspecific and intraspecific communication. However, there are some factors (preparation process and lack of target) which can limit the antibiofilm impact of postbiotics. Therefore, by using a delivery carrier and optimizing process parameters, the effect of interfering factors can be eliminated. This review summarizes the concept and characteristics of postbiotics from LAB, focusing on their preparation technology and antibiofilm effect, and the applications and limitations of postbiotics in food processing and clinical treatment are also discussed.

A Multi-Modal Deep-Learning Air Quality Prediction Method Based on Multi-Station Time-Series Data and Remote-Sensing Images: Case Study of Beijing and Tianjin

The profound impacts of severe air pollution on human health, ecological balance, and economic stability are undeniable. Precise air quality forecasting stands as a crucial necessity, enabling governmental bodies and vulnerable communities to proactively take essential measures to reduce exposure to detrimental pollutants. Previous research has primarily focused on predicting air quality using only time-series data. However, the importance of remote-sensing image data has received limited attention. This paper proposes a new multi-modal deep-learning model, Res-GCN, which integrates high spatial resolution remote-sensing images and time-series air quality data from multiple stations to forecast future air quality. Res-GCN employs two deep-learning networks, one utilizing the residual network to extract hidden visual information from remote-sensing images, and another using a dynamic spatio-temporal graph convolution network to capture spatio-temporal information from time-series data. By extracting features from two different modalities, improved predictive performance can be achieved. To demonstrate the effectiveness of the proposed model, experiments were conducted on two real-world datasets. The results show that the Res-GCN model effectively extracts multi-modal features, significantly enhancing the accuracy of multi-step predictions. Compared to the best-performing baseline model, the multi-step prediction's mean absolute error, root mean square error, and mean absolute percentage error increased by approximately 6%, 7%, and 7%, respectively.

Opposite regulation effects of Al3+ on different types of carbon quantum dots and potential applications in information encryption

Regulating the photoluminescence (PL) of carbon quantum dots (CQDs) through ion modification is a well-established and effective approach. Herein, we report the opposite regulation effects of Al3+ ions on the PL properties of two distinct types of CQDs (graphene quantum dots, GQDs, and nitrogen-doped carbon quantum dots of 2,3-diaminophenazine, DAP), and elucidate the underlying mechanism of the binding of Al3+ ions to different PL sites on CQDs by employing ultraviolet-visible spectroscopy, X-ray photoelectron spectroscopy, and density functional theory calculations. Specifically, Al3+ ions are primarily situated around the oxygen-containing groups, which do not impact the π-π regions of GQDs. However, Al3+ ions are preferentially adsorbed on the top of pyridine nitrogen in the phenazine rings of DAP, thus reducing the PL regions of DAP. Based on the opposite PL effects of Al3+ on GQDs and DAP, we explore potential applications of information encryption and successfully realize multi-level information encryption and decryption, which may provide new strategies for CQDs in information security.

Ternary-Metal Sn-Pb-Zn Perovskite to Reconstruct Top Surface for Efficient and Stable Less-Pb Perovskite Solar Cells

Though Sn-Pb alloyed perovskite solar cells (PSCs) achieved great progress, there is a dilemma to further increase Sn for less-Pb requirement. High Sn ratio (>70%) perovskite exhibits nonstoichiometric Sn:Pb:I at film surface to aggravate Sn2+ oxidation and interface energy mismatch. Here, ternary metal alloyed (FASnI3 )0.7 (MAPb1- x Znx I3 )0.3 (x = 0-3%) is constructed for Pb% < 30% perovskite. Zn with smaller ionic size and stronger ionic interaction than Sn/Pb assists forming high-quality perovskite film with ZnI6 4- enriched at surface to balance Sn:Pb:I ratio. Differing from uniform bulk doping, surface-rich Zn with lower lying orbits pushes down the energy band of perovskite and adjusts the interface energy for efficient charge transfer. The alloyed PSC realizes efficiency of 19.4% at AM1.5 (one of the highest values reported for Pb% < 30% PSCs). Moreover, stronger bonding of Zn─I and Sn─I contributes to better durability of ternary perovskite than binary perovskite. This work highlights a novel alloy method for efficient and stable less-Pb PSCs.

Establishment of hypertension risk nomograms based on physical fitness parameters for men and women: a cross-sectional study

Objective

This study aims to establish hypertension risk nomograms for Chinese male and female adults, respectively.

Method

A series of questionnaire surveys, physical assessments, and biochemical indicator tests were performed on 18,367 adult participants in China. The optimization of variable selection was conducted by running cyclic coordinate descent with 10-fold cross-validation through the least absolute shrinkage and selection operator (LASSO) regression. The nomograms were built by including the predictors selected through multivariable logistic regression. Calibration plots, receiver operating characteristic curves (ROC), decision curve analysis (DCA), clinical impact curves (CIC), and net reduction curve plots (NRC) were used to validate the models.

Results

Out of a total of 18 variables, 5 predictors-namely age, body mass index, waistline, hipline, and resting heart rate-were identified for the hypertension risk predictive model for men with an area under the ROC of 0.693 in the training set and 0.707 in the validation set. Seven predictors-namely age, body mass index, body weight, cardiovascular disease history, waistline, resting heart rate, and daily activity level-were identified for the hypertension risk predictive model for women with an area under the ROC of 0.720 in the training set and 0.748 in the validation set. The nomograms for both men and women were externally well-validated.

Conclusion

Gender differences may induce heterogeneity in hypertension risk prediction between men and women. Besides basic demographic and anthropometric parameters, information related to the functional status of the cardiovascular system and physical activity appears to be necessary.

Rapid screening based on machine learning and molecular docking of umami peptides from porcine bone

BACKGROUND

The traditional screening method for umami peptide, extracted from porcine bone, was labor-intensive and time-consuming. In this study, the rapid screening method and molecular mechanism of umami peptide was investigated.

RESULTS

This article showed that a more precisely rapid screening method with composite machine learning and molecular docking was used to screen the potential umami peptide from porcine bone. As reference, 24 reported umami peptides were predicated by composite machine learning, with the accuracy of 86.7%. In this study, potential umami peptide sequences from porcine bone were screened by UMPred-FRL, Umami-MRNN Demo, and molecular docking was used to provide further screening. Finally, nine peptides were screened and verified as umami peptides by this method: LREY, HEAL, LAKVH, FQKVVA, HVKELE, AEVKKAP, EAVEKPQS, KALSEEL and KKMFETES. The hydrogen bonding was deemed to be the main interaction force with receptor T1R3, and domain binding sites were Ser146, His121 and Glu277. The result demonstrated the feasibility of machine learning assisted T1R1/T1R3 receptor for rapid screening umami peptides. The screening method would not only adapt to screen umami peptides from porcine bone but possibly applied for other sources. It also provided a reference for rapid screening of umami peptides.

CONCLUSION

The manuscript lays a rapid screening method in screening umami peptide, and nine umami peptides from porcine bone were screened and identified. © 2022 Society of Chemical Industry.

Spatial distribution of gut microbiota in mice during the occurrence and remission of hyperuricemia

BACKGROUND

Previous studies have shown that anserine can alleviate hyperuricemia by changing the fecal microbiota of hyperuricemic mice.

TOPIC

However, the fecal microbiota could not fully represent the distribution of the whole gut microbiota. Knowing the spatial distribution of the gastrointestinal tract microbiota is therefore important for understanding its action in the occurrence and remission of hyperuricemia.

METHODS

This study provides a comprehensive map of the most common bacterial communities that colonize different parts of the mouse gastrointestinal tract (stomach, duodenum, ileum, cecum, and colon) using a modern methodological approach.

RESULTS

The stomach, colon, and cecum showed the greatest richness and diversity in bacterial species. Three clusters of bacterial populations were observed along the digestive system: (1) in the stomach, (2) in the duodenum and ileum, and (3) in the colon and cecum. A high purine solution changed the composition and abundance of the digestive tract microbiota, and anserine relieved hyperuricemia by restoring the homeostasis of the digestive tract microbiota, especially improving the abundance of probiotics in the digestive tract.

IMPLICATION

This could be the starting point for further research on the regulation of hyperuricemia by gut microbiota with the ultimate goal of promoting health and welfare. © 2022 Society of Chemical Industry.

Ag NC and Ag NP/PorC Film-Based Surface-Enhanced Raman Spectroscopy-Type Immunoassay for Ultrasensitive Prostate-Specific Antigen Detection

Surface-enhanced Raman scattering (SERS) is a spectral detection technology with high sensitivity and detectivity and can be used to detect the fingerprint information of the molecules with ultralow concentration. Herein, a kind of immunostructure constructed by Ag nanoparticle/porous carbon (Ag NP/PorC) films as the immunosubstrate and Ag NCs as the immunoprobes was presented for ultralow level prostate-specific antigen (PSA) detection. Experimentally, the Ag NP/PorC film was first prepared with a facile method by carbonizing the gelatin-AgNO₃ film in air, and Ag NCs were synthesized by the hydrothermal method. Then, the Ag NP/PorC film was modified by PSA antibodies as the substrate, while Ag NCs were decorated by R6G and PSA antibodies for probes. The sandwiched SERS detection embodiment was constructed by the immunoreaction between the PSA and PSA antibody predecorated on the substrate and probes. Our results show that the proposed SERS-type immunoassay is highly sensitive and selective to a wide range of PSA concentrations from 10^-5 to 10^-12 g/mL. Thereafter, it was also implemented to detect the PSA level in human serum, and the results successfully reproduce the PSA levels as those measured by the chemiluminescence method with a recovery rate above 90%. All in all, this SERS-type immunoassay provides a promising method for the early diagnosis of prostate cancer.

The roles and mechanisms of circular RNAs related to mTOR in cancers

BACKGROUND

Circular RNAs (circRNAs) are stable molecules with covalently closed structures that have an irreplaceable role in the occurrence, progression, and even treatment of plenty of cancers. Mammalian/mechanistic target of rapamycin (mTOR) is a key regulator in cancers and plays several biological functions, such as proliferation, migration, invasion, autophagy, and apoptosis.

METHODS

All data were collected through PubMed and CNKI, using terms including "circRNA," "mTOR," "caner," "signaling pathway," "biomarker," "diagnosis," "treatment." Articles published in Chinese and English were included.

RESULTS

In this review, the expression, function, and mechanism of circRNA-associated mTOR in cancers were described. CircRNA-associated-mTOR can regulate the progression and therapy of a variety of cancers in multiple signaling pathways, such as phosphatidylinositol-3-kinase (PI3K)/protein kinase B (Akt)/mTOR, mitogen-activated protein kinase (MAPK)/mTOR, and AMP-activated protein kinase (AMPK)/mTOR axis. These cancers including esophageal carcinoma (circLPAR3, ciRS-7), gastric cancer (circNRIP1, hsa_circ_0010882, hsa_circ_0000117, hsa_circ_0072309, and circST3GAL6), colorectal cancer (hsa_circ_0000392, hsa_circ_0084927, hsa_circ_0104631, and circFBXW7), liver cancer (circC16orf62, hsa_circ_100338, hsa_circ_0004001, hsa_circ_0004123, hsa_circ_0075792, hsa_circ_0079299, and hsa_circ_0002130), pancreatic cancer (circ-IARS and circRHOBTB3), renal carcinoma (ciRS-7), bladder cancer (circUBE2K), prostate cancer (circMBOAT2 and circ-ITCH), ovarian cancer (circEEF2, circRAB11FIP1, circMYLK, and circTPCN), endometrial cancer (hsa_circ_0002577 and circWHSC1), lung cancer (circHIPK3, hsa_circ_0001666), thyroid cancer (hsa_circ_0007694 and hsa_circ_0008274), glioma (circGFRA1, circ-MAPK4, circPCMTD1, and hsa_circ_0037251), osteosarcoma (circTCF25), leukemia (circ-PRKDC), and breast cancer (hsa_circ_0000199, circUBAP2, and circWHSC1).

Sensitivity Analysis of a Bench-Scale Pyrolysis Model for Composite Materials: A Case Study of Poly(lactic acid)/Melamine/Ammonium Polyphosphate

On the basis of a well-developed bench-scale pyrolysis model that relates material composition to flammability, this paper applied mathematical simulations to explore the model sensitivity for the prediction of fire behavior of composite materials. A pyrolysis model for poly(lactic acid) blended with melamine and ammonium polyphosphate as the reference material was selected as the case for analysis. The model input parameters for simulations include the heat of reaction, apparent activation energy, and pre-exponential factor of 15 reactions, as well as the thermal conductivity, emissivity coefficient, absorption coefficient, and density of 17 condensed-phase components. Each reaction-related or component-related parameter was adjusted from 80% of the model value to 120% with a 5% or 10% gradient. Finally, 826 simulation cases in total were calculated for analysis. Both the mass loss rate and the heat release rate of each case were calculated to characterize the sensitivity, which showed the same pattern. Finally, seven primary reactions and five key condensed-phase components with high sensitivity were identified. The predicted fire behaviors are highly related to the kinetics of the reactions between virgin components or reactions where virgin components play an important role in, including the pyrolysis of melted poly(lactic acid), the first step in the pyrolysis of melamine, the first step in the pyrolysis of ammonium polyphosphate, the reaction between melted poly(lactic acid) and melamine, the reaction between ammonium polyphosphate and melamine, and further decomposition of the generated new condensed-phase component. Particularly, the activation energy of these reactions is of sensitivity larger than 5% or 15%. The heat of decomposition of pyrolysis of melted poly(lactic acid) also showed a sensitivity of 2%-5%. The pre-exponential factor of all reactions showed a sensitivity of less than 2%, which can be ignored. Inputting the proper density is important for the prediction of fire behavior as the sensitivity is larger than 2%. The sensitivity of the milligram-scale model was also processed and compared. These simulations provided a fundamental understanding of the sensitivity of thermophysical and chemical properties and thus provide advanced insights into fire behavior modeling and new composite material design.

Nonlinear Dynamic Soft Sensor Development with a Supervised Hybrid CNN-LSTM Network for Industrial Processes

A soft sensor is a key component when a real-time measurement is unavailable for industrial processes. Recently, soft sensor models based on deep-learning techniques have been successfully applied to complex industrial processes with nonlinear and dynamic characteristics. However, the conventional deep-learning-based methods cannot guarantee that the quality-relevant features are included in the hidden states when the modeling samples are limited. To address this issue, a supervised hybrid network based on a dynamic convolutional neural network (CNN) and a long short-term memory (LSTM) network is designed by constructing multilayer dynamic CNN-LSTM with improved structures. In each time instant, data augmentation is implemented by dynamic expansion of the original samples. Moreover, multiple supervised hidden units are trained by adding quality variables as part of the layer input to acquire a better quality-related feature learning performance. The effectiveness of the proposed soft senor development is validated through two industrial applications, including a penicillin fermentation process and a debutanizer column.

Contributions of Various Cd(II) Adsorption Mechanisms by Phragmites australis-Activated Carbon Modified with Mannitol

Due to its high toxicity, persistence, and bioaccumulation in the food chain, controlling cadmium (Cd) pollution in wastewater is urgent. Activated carbon is a popular material for removing Cd. To improve the Cd(II) adsorption efficiency by increasing the number of oxygen-containing functional groups, Phragmites australis-activated carbon (PAAC) was modified with mannitol at a low temperature (150 °C). The textural and chemical characteristics of PAAC and modified PAAC (M-PAAC) were analyzed by surface area analysis, elemental analysis, Boehm's titration, Fourier-transform infrared spectroscopy, and X-ray photoelectron spectroscopy. Batch adsorption experiments were conducted to investigate the influence of Cd(II) concentration, contact time, ionic strength, and pH on Cd(II) adsorption. The main adsorption mechanisms of Cd(II) on activated carbon were quantitatively calculated. The results showed that mannitol modification slightly decreased the S _BET (5.30% of PAAC) and increased the content of carboxyl, lactone, and phenolic groups (total increase of 43.96% with PAAC), which enhanced the adsorption capacity of PAAC by 58.59%. The adsorption isotherms of PAAC and M-PAAC were described well using the Temkin model, while the intraparticle diffusion model fitted the Cd(II) adsorption kinetics best. Precipitation with minerals was a crucial factor for Cd(II) adsorption on activated carbon (50.40% for PAAC and 40.41% for M-PAAC). Meanwhile, the Cd(II) adsorption by M-PAAC was also dominated by complexation with oxygen-containing functional groups (33.60%). This research provides a method for recovering wetland plant biomass to prepare activated carbon and efficiently treat Cd-containing wastewater.

Optimization of a Rolling Triboelectric Nanogenerator Based on the Nano-Micro Structure for Ocean Environmental Monitoring

The serious environmental pollution and energy crisis have become a global issue, which makes it a pressing task to develop sustainable and clean energy sources. There exists a large amount of renewable energy in the ocean; unfortunately, most resources are underutilized. In this work, we demonstrate a performance-enhancing rolling triboelectric nanogenerator (TENG) based on nano-micro-structured polytetrafluoroethylene (PTFE) films. The nano-micro structure on the PTFE surface can increase the effective contact area and enhance the triboelectric effect, which is beneficial to improve the output performance. As a result, the output voltage and output current are 25.1 V and 7.3 μA, respectively. We further investigate the effect of nano-micro PTFE concentration on the output performance. The TENG based on a 45% concentration of nano-micro PTFE presents the maximum output power. Furthermore, this TENG can effectively harvest water wave energy with various amplitudes and frequencies, which has the potential to harvest ocean energy for environmental monitoring.

TiO2-Based photocatalyst modified with a covalent triazine-based framework organocatalyst for carbamazepine photodegradation

A novel fluorine-doped TiO2 (TiO2-X F X ) heterojunction semiconductor photocatalyst was synthesised using covalent triazine-based frameworks (CTFs) at different weight ratios. X-ray photoelectron spectroscopy revealed that doping with CTFs shifts the value of the TiO2-X F X catalyst to a lower binding energy, which led to the bandgap narrowing. From the results of the photocatalytic activity and Fourier-transform infrared spectroscopy, a rise in carbamazepine (CBZ) adsorption under dark conditions and an increased intensity of characteristic triazine units after exfoliation were observed, which indicated that the addition of nanosheet CTFs would increase the number of active sites. Furthermore, the results showed that the TiO2-X F X /CTFs photocatalyst was almost 5.5 times better than pure TiO2-X F X in the removal of CBZ under visible light owing to the narrowed bandgap, the increased active sites, the quick separation of photo-generated carriers, and improved light absorption. A mechanism for photodegradation of CBZ with the TiO2-X F X /CTFs photocatalyst was proposed.

Japanese encephalitis virus-primed CD8+ T cells prevent antibody-dependent enhancement of Zika virus pathogenesis

Cross-reactive anti-flaviviral immunity can influence the outcome of infections with heterologous flaviviruses. However, it is unclear how the interplay between cross-reactive antibodies and T cells tilts the balance toward pathogenesis versus protection during secondary Zika virus (ZIKV) and Japanese encephalitis virus (JEV) infections. We show that sera and IgG from JEV-vaccinated humans and JEV-inoculated mice cross-reacted with ZIKV, exacerbated lethal ZIKV infection upon transfer to mice, and promoted viral replication and mortality upon ZIKV infection of the neonates born to immune mothers. In contrast, transfer of CD8+ T cells from JEV-exposed mice was protective, reducing the viral burden and mortality of ZIKV-infected mice and abrogating the lethal effects of antibody-mediated enhancement of ZIKV infection in mice. Conversely, cross-reactive anti-ZIKV antibodies or CD8+ T cells displayed the same pathogenic or protective effects upon JEV infection, with the exception that maternally acquired anti-ZIKV antibodies had no effect on JEV infection of the neonates. These results provide clues for developing safe anti-JEV/ZIKV vaccines.

Effects of dietary tuna dark muscle enzymatic hydrolysis and cooking drip supplementations on growth performance, antioxidant activity and gut microbiota modulation of Bama mini-piglets

Experiments were conducted to evaluate the enzymatic hydrolysis of tuna dark muscle (EH-TDM) and cooking drip (EH-TCD) as nutrition supplements in Bama mini-piglets. Our results showed that EH-TDM treatment produce considerable benefits for the Bama mini-piglets in terms of the feed efficiency, the prevention of oxidative damage and the control of blood lipid levels. The EH-TCD treatment also improved the growth performance, whereas all other aspects deteriorated. The analyses of the gut microbiota revealed an increased proportion of bacteria involved in energy metabolism and protein utilization in these two groups. Furthermore, short chain fatty acid producing bacteria were increased, as well as the genera Lactobacillus and Bifidobacterium, which are involved in intestinal dysfunction regulation. This study will provide valuable information for the development of marine protein hydrolysates as feed ingredients for the swine industry.

Direct study of the electrical properties of PC12 cells and hippocampal neurons by EFM and KPFM

Electrical related properties play important roles in biological structures and functions. Herein, the capacitance gradient and local contact potential difference (CPD) of cell bodies and processes of PC12 cells (representative cells of the sympathetic nervous system), hippocampal neurons (representative cells of the central nervous system) and spines were investigated by Electrostatic Force Microscopy (EFM) and Kelvin Probe Force Microscopy (KPFM) at high lateral spatial resolution directly. The results demonstrate that the capacitance gradients of cell bodies, processes and spines of PC12 cells and hippocampal neurons are very close (in the range of 19-23 zF nm-1) and fit well with the theoretical calculation results (21.7 zF nm-1). This indicates that the differences of nerve signal activities and functions of the sympathetic and central nervous systems are not related to the electric polarization properties. The CPD of cell bodies and processes of PC12 cells is smaller than that of hippocampal neurons. The CPD of spines is much more negative than that of the cell bodies and processes. These results reveal that the surface potential is closely related to the neural signal transduction functions, and spines play vital roles in neural signal transmission. This work indicates the similarity (capacitance gradient) and differences (surface potential) of the electrical properties between the sympathetic and central nervous systems for the first time. The methods and results of this work are useful in the further study of the electrical properties in cellular activities and physiological processes.

In vitro evaluation of the toxicity and underlying molecular mechanisms of Janus Fe3 O4 -TiO2 nanoparticles in human liver cells

Recent studies show that Janus Fe3 O4 -TiO2 nanoparticles (NPs) have potential applications as a multifunctional agent of magnetic resonance imaging (MRI) and photodynamic therapy (PDT) for the diagnosis and therapy of cancer. However, little work has been done on their biological effects. To evaluate the toxicity and underlying molecular mechanisms of Janus Fe3 O4 -TiO2 nanoparticles, an in vitro study using a human liver cell line HL-7702 cells was conducted. For comparison, the Janus Fe3 O4 -TiO2 NPs parent material TiO2 NPs was also evaluated. Results showed that both Fe3 O4 -TiO2 NPs and TiO2 NPs decreased cell viability and ATP levels when applied in treatment, but increased malonaldehyde (MDA) and reactive oxygen species (ROS) generation. Mitochondria JC-1 staining assay showed that mitochondrial membrane permeability injury occurred in both NPs treated cells. Cell viability analysis showed that TiO2 NPs induced slightly higher cytotoxicity than Fe3 O4 -TiO2 NPs in HL7702 cells. Western blotting indicated that both TiO2 NPs and Fe3 O4 -TiO2 NPs could induce apoptosis, inflammation, and carcinogenesis related signal protein alterations. Comparatively, Fe3 O4 -TiO2 NPs induced higher signal protein expressions than TiO2 NPs under a high treatment dose. However, under a low dose (6.25 μg/cm2 ), neither NPs had any significant toxicity on HL7702 cells. In addition, our results suggest both Fe3 O4 -TiO2 NPs and TiO2 NPs could induce oxidative stress and have a potential carcinogenetic effect in vitro. Further studies are needed to elaborate the detailed mechanisms of toxicity induced by a high dose of Fe3 O4 -TiO2 NPs.

Network capacity with probit-based stochastic user equilibrium problem

Among different stochastic user equilibrium (SUE) traffic assignment models, the Logit-based stochastic user equilibrium (SUE) is extensively investigated by researchers. It is constantly formulated as the low-level problem to describe the drivers' route choice behavior in bi-level problems such as network design, toll optimization et al. The Probit-based SUE model receives far less attention compared with Logit-based model albeit the assignment result is more consistent with drivers' behavior. It is well-known that due to the identical and irrelevant alternative (IIA) assumption, the Logit-based SUE model is incapable to deal with route overlapping problem and cannot account for perception variance with respect to trips. This paper aims to explore the network capacity with Probit-based traffic assignment model and investigate the differences of it is with Logit-based SUE traffic assignment models. The network capacity is formulated as a bi-level programming where the up-level program is to maximize the network capacity through optimizing input parameters (O-D multiplies and signal splits) while the low-level program is the Logit-based or Probit-based SUE problem formulated to model the drivers' route choice. A heuristic algorithm based on sensitivity analysis of SUE problem is detailed presented to solve the proposed bi-level program. Three numerical example networks are used to discuss the differences of network capacity between Logit-based SUE constraint and Probit-based SUE constraint. This study finds that while the network capacity show different results between Probit-based SUE and Logit-based SUE constraints, the variation pattern of network capacity with respect to increased level of travelers' information for general network under the two type of SUE problems is the same, and with certain level of travelers' information, both of them can achieve the same maximum network capacity.