Interference Of Other Factors Research Articles

A novel semi-empirical soil multi-factor radiative transfer model for soil organic matter estimation based on hyperspectral imagery

Soil organic matter (SOM) concentration is an important factor affecting soil quality, and rapid and wide-scale monitoring of SOM concentration is a key step toward sustainable agriculture. Hyperspectral technology is widely used in soil composition monitoring, due to its rich spectral information. The complex imaging environment of hyperspectral imagery and the mixed pixel problem have led to the current applications of soil condition estimation mostly using data-driven methods. However, the estimation process based on data-driven methods cannot be explained by radiative transfer theory. Therefore, in this paper, a semi-empirical soil multi-factor radiative transfer (SESMRT) model combining a soil radiative transfer model and data-driven model is proposed for SOM estimation based on hyperspectral imagery. The radiative transfer model in the SESMRT model fully considers the soil components, such as SOM, soil moisture, soil iron oxides, and particle size distribution, and achieves high-precision simulation of soil spectra by resolving the mechanism of the influence of soil components on spectra. The SOM spectra calculated by the radiative transfer model are then used to estimate the SOM concentration based on a data-driven model. The SOM spectra eliminate the interference of other factors in the spectrum and significantly enhance the correlation between the spectrum and SOM. Thus, the SOM concentration can be estimated with a high degree of accuracy (R2 = 0.660 ± 0.034, RMSE = 3.923 ± 0.236, RPIQ = 2.003 ± 0.118 for GF5 and R2 = 0.685 ± 0.030, RMSE = 3.543 ± 0.311, RPIQ = 2.309 ± 0.207 for HyMap). Finally, the comparison of the estimated results for 2017 and 2019 shows that the SOM concentration of the cultivated soils in the study area increased, while the opposite is observed for the soils around the mining areas.

Structural comparison of different isolated eucalyptus lignins and analysis of their interaction mechanism with bovine serum albumin solution under QCM-D

Abstract In this study, representative lignin samples differing in hydroxyl content, molecular weight, linkage composition and lignin units ratio were prepared from eucalyptus wood by different isolation means and modification means: milled wood lignin (MWL), kraft lignin classified at different pH (KL), lignocresol (LC), lignoresorcinol (LR), lignopyrogallol (LP) as well as lignocresol secondary functional switched samples (LC 2ndderiv). The structure of various lignins was characterized in detail by Fourier transform infrared (FT-IR) spectroscopy, gel permeation chromatography (GPC) and nuclear magnetic resonance (NMR). In order to eliminate the interference of other factors, bovine serum albumin (BSA) with relatively simple protein structure and different kinds of lignin and their derivatives were selected as the research objects. The adsorption/desorption behavior and mechanism between lignin samples and BSA were studied by quartz crystal microbalance with dissipation monitoring (QCM-D). The results showed that the content of phenolic hydroxyl was the main factor affecting the interaction of lignin and BSA, but in addition, the molecular size, linkages composition and the types of lignin units also had important effects on its adsorption behavior. The research will provide theoretical guidance and all-round reliable basic data for the interaction of lignin on lignocellulose hydrolysis enzymes in industrial application.

Deep Learning-Based Semantic Segmentation Methods for Pavement Cracks

As road mileage continues to expand, the number of disasters caused by expanding pavement cracks is increasing. Two main methods, image processing and deep learning, are used to detect these cracks to improve the efficiency and quality of pavement crack segmentation. The classical segmentation network, UNet, has a poor ability to extract target edge information and small target segmentation, and is susceptible to the influence of distracting objects in the environment, thus failing to better segment the tiny cracks on the pavement. To resolve this problem, we propose a U-shaped network, ALP-UNet, which adds an attention module to each encoding layer. In the decoding phase, we incorporated the Laplacian pyramid to make the feature map contain more boundary information. We also propose adding a PAN auxiliary head to provide an additional loss for the backbone to improve the overall network segmentation effect. The experimental results show that the proposed method can effectively reduce the interference of other factors on the pavement and effectively improve the mIou and mPA values compared to the previous methods.

An LSTM-based adaptive prediction control model for the wire diameter control of high-precision optical fiber drawing machines

Reducing inconsistencies in fiber diameter has always been a focus of research on optical fiber drawing machines (OFDM). Based on an established mathematical model for OFDM, we adopted a long short-term memory (LSTM)-based neural network to predict fiber wire diameter and utilized these results to feedback and control the drawing speed, thereby achieving high precision control of the wire diameter. We trained the proposed network using relevant data from two different fiber drawing processes, allowing it to learn the long-term and short-term correlations in the data. Additionally, we evaluated the performance of the model using root mean square error (RMSE) and R2 as indicators. The experimental results show that network complexity has a considerable impact on the precision of fiber wire diameter prediction. We also established that two LSTM hidden layers with 64 neural units in each layer are the most suitable for the proposed network structure. The network with such a structure has the smallest RMSE value in the validation set and the largest R2 in the testing set. Subsequently, the optimal network structure was used to conduct a multi-timespan wire diameter prediction experiment. According to the experimental results, the LSTM-based wire diameter prediction model still has a satisfactory predictive effect when the time is as long as 50 s, suggesting that the precision and robustness of this network are high. When this method is applied to the actual wire drawing process, the wire diameter error can be controlled to within ± 1.8 μm when the target wire diameter is 0.66 mm, indicating that the wire diameter precision is greatly enhanced. Results indicate that using LSTM-based prediction and control effectively avoids the interference of other factors in the process of wire drawing. Therefore, we remedied the time delay issue of conventional wire diameter control methods. Also, compared with conventional methods, we achieved more precise and robust control of wire diameter.

Effective Dose of Prophylactic Norepinephrine for Preventing Hypotension under Combined Spinal and Epidural Anesthesia during Cesarean Section in Singleton Versus Twin Pregnancies

To determine and compare the 90% effective dose (ED 90) of prophylactic infusion of norepinephrine for preventing hypotension during combined spinal-epidural anesthesia for cesarean section in singleton versus twin pregnancies. A randomized controlled trial was conducted, enrolling 200 pregnant women, 100 of which were of singleton pregnancies while the other 100 were of twin pregnancies, at West China Second University Hospital, Sichuan University between November 3, 2020 and June 2, 2021. All 200 subjects were to have Cesarean section under combined spinal-epidural anesthesia. By using a random number table, they were randomly assigned to five groups, receiving norepinephrine at the infusion dosage of 0.025, 0.050, 0.075, 0.100, and 0.125 μg/(kg·min), with 20 subjects of singleton pregnancy and 20 subjects of twin pregnancy in each group. Norepinephrine infusion started when the anesthesiologist initiated the spinal anesthetic injection and lasted until the delivery of the fetus. The primary outcome measure was the incidence of maternal hypotension during combined spinal-epidural anesthesia, up until the delivery of the fetus. Survival analysis, with survival being defined as not having hypotension, of the incidence of hypotension among the subjects was conducted. Probit regression was used to determine the ED 90 of norepinephrine, as well as the corresponding 95% confidence interval ( CI), for preventing hypotension during cesarean delivery under combined spinal-epidural anesthesia in women with singleton and twin pregnancies. There was no significant difference in the baseline data or the anesthesia and operation data between pregnant women of singleton pregnancy and those of twin pregnancy ( P>0.05). In singleton pregnant women receiving 0.025, 0.05, 0.075, 0.1 and 0.125 μg/(kg·min) of norepinephrine, the incidence of hypotension was 50% (10/20), 35% (7/20), 20% (4/20), 10% (2/20) and 5% (1/20), respectively. The estimated ED 90 of prophylactic norepinephrine for preventing hypotension during anesthesia was 0.100 (95% CI, 0.082-0.130) μg/(kg·min). In twin pregnant women receiving 0.025, 0.05, 0.075, 0.1 and 0.125 μg/(kg·min) of norepinephrine, the corresponding incidence of hypotension was 60% (12/20), 20% (4/20), 20% (4/20), 10% (2/20) and 5% (1/20). The estimated ED 90 of norepinephrine for preventing hypotension during anesthesia was 0.098 (95% CI, 0.080-0.127) μg/(kg·min). Survival analysis showed significant difference in the incidence of hypotension among the five groups receiving different infusion doses in singleton pregnancy subjects, and the same is true of the twin pregnancy subjects ( P<0.05). The incidence of reactive hypertension increased with increasing dosage of norepinephrine in both singleton pregnancy subjects and twin pregnancy subjects ( P<0.05). There was no significant difference in the incidence of other maternal adverse reaction or in neonatal outcomes in singleton and twin pregnancy subjects receiving different dosage of norepinephrine ( P>0.05). The gestational weeks, weight, and BMI were significantly different ( P<0.05), while the other characteristics, including age and height, were comparable ( P>0.05) between singleton and twin pregnancy subjects receiving norepinephrine at the same dosage. There was no significant difference in the incidence of hypotension, reactive hypertension, bradycardia, nausea and vomiting, and dizziness between singleton and twin pregnancy subjects receiving the same dose ( P>0.05). Survival analysis displayed no significant difference in the incidence of hypotension between singleton and twin pregnancy subjects receiving norepinephrine at the same dosage ( P>0.05). There was no significant difference in the ED 90 of norepinephrine between women with singleton pregnancies and those with twin pregnancies ( P>0.05). There was no significant difference in the ED 90 of norepinephrine for preventing hypotension during combined spinal-epidural anesthesia between women with singleton pregnancy and those with twin pregnancy. Interference of other factors, including gestational age, body mass, and BMI should be considered in clinical practice.

Ratiometric detection of polymyxin B based on the disaggregation of pyrenyl nanoassemblies in 100% aqueous media

Polymyxin B (PMB) was an antibiotic with highly effective antibacterial effect but narrow safety interval, and its residues in food had attracted widespread attention. It was important to develop an accurate method for the rapid detection of PMB in animal foods. In this work, we had established a ratiometric sensing system based on the formation of supramolecular assemblies of pyrenyl probes, which were driven by the synergy of noncovalent forces such as multiple-electrostatic and π-π stacking interactions. Compared with the traditional fluorescence detection based on the single wavelength change, the present approach showing two-wavelength fluorescence response could reduce the interference of other factors making the experimental results more accurate. The sensor exhibited high sensitivity and selectivity with a low detection limit (28.3 nM). This method could be used to realize visual detection and had a visual detection limit of 1 μM. As we had learned yet, this was the first ratiometric sensor for PMB detection in aqueous solution. We believed all our preliminary would not only provide a complementary strategy for the detection of PMB, but also develop some new ideas for the construction of sensors for rapid antibiotic detection.

Evaluation on the Impact of Cache Parameter Selection in Access-Driven Cache Attacks

Cache attacks exploit the hardware vulnerabilities inherent to modern processors and pose a new threat to Internet of Things (IoT) devices. Intuitively, different cache parameter configurations directly impact the attack effectiveness, but the current research on this issue is not systematic or comprehensive enough. This paper’s primary focus is to evaluate how different cache parameter configurations affect access-driven attacks. We build a flexible and configurable simulation verification environment based on the Chipyard framework. To reduce the interference of other factors, we established a baseline for each category of parameter evaluation. We propose a novel evaluation model, called Key Score Scissors Differential (KSSD), for evaluating common private and shared cache parameters under the local and cross-core attack models, respectively; among these are private cache replacement policy, private cache capacity, cache line size, private cache associativity, shared cache capacity, and shared cache associativity. Ours is the first evaluation of the shared cache under a cross-core attack model. As a result of the evaluation, the quantitative metrics can provide a reliable indication of information leakage level under the current cache configuration, which is helpful for attackers, defenders, and evaluators. Furthermore, we provide detailed explanations and discussions of inconsistent findings by comparing our results with the existing literature.

A novel ratiometric fluorescent probe for the detection of nickel ions in the environment and living organisms

Nickel resources are abundant in the world, and the application of nickel in production and life is more and more extensive. However, excessive nickel entering the environment will not only cause environmental pollution but also seriously endanger plants, animals and human health. Nickel compounds are carcinogenic and have been classified as a class 1 carcinogen. Nickel mainly exists in the form of divalent ions in the environment. However, there are few simple and effective methods for the detection of nickel ions, and these methods still have certain limitations. At present, the mechanisms of nickel influence in organisms are also unclear. Therefore, we constructed a ratiometric fluorescent probe Ra-Ni, which can achieve its own self-calibration and avoid the interference of other factors, thereby realizing the specific identification of nickel ions. The probe can detect nickel ions sensitively with a detection limit as low as 26.2 nM and can respond in a short time (< 2 min), which proves the great potential of the probe in the detection of nickel ions. At the same time, Ra-Ni has also been successfully used for imaging nickel ions in living cells and zebrafish, providing an effective tool for the study of physiological and pathological processes. The detection effect of nickel ions in actual water sample is also satisfactory, which further demonstrates the practicability of Ra-Ni in environmental applications.

The Association Between Metabolic Syndrome and Prostate Cancer Risk: A Large-Scale Investigation and Study of Chinese.

BackgroundTo investigate the association between metabolic syndrome (MetS) and its components and prostate cancer (PCa).MethodsThis study enrolled 482 943 consecutive men who underwent routine health checkups at the Health Management Center of West China Hospital Between 2010 and 2017. For patients with elevated prostate-specific antigen (PSA) levels or color Doppler ultrasound indicating abnormal prostates, we recommended prostate puncture and follow-up. We used the chi-square test and independent t-test for categorical variables and continuous variables, respectively. We used logistic regression analysis to evaluate the effects of MetS and its components on prostate cancer risk.ResultsWe found that the incidence of PCa in Chinese men over 40 years of age was 0.1%. Among the 85882 participants, 31.5% (27016/85882) of the patients were diagnosed with MetS. PCa was associated with older age, higher PSA levels, lighter weight and shorter height, hypertension, elevated fasting blood glucose (FBG) and HDL cholesterol level, lower triglycerides. After excluded the interference of other factors in multivariate logistic analysis, we found that MetS, hypertension, hyperlipidemia, hyperglycemia, and obesity were not related to the risk of PCa. High age and PSA levels were risk factors for prostate cancer.ConclusionsHigh age and PSA levels were risk factors for prostate cancer. MetS, hypertension, hyperlipidemia, hyperglycemia, and obesity were not related to the risk of PCa.

Synthesis and Characterization of a Mixed Nanofertilizer Influencing the Nutrient Use Efficiency, Productivity, and Nutritive Value of Tomato Fruits.

Due to the higher potential for enhancing nutrient use efficiency, nanofertilizer (NF) is crucial in sustainable crop production. Thus, foliar-applied mixed nanofertilizer (MNFf) and commercial fertilizer (CF) into the soil (CFs) were claimed together ([MNFf + CFs]) and comparative nutrient use efficiency (NUE), productivity, and nutritional properties of tomato fruits were investigated. The mixed nanofertilizer (MNF) was prepared in our laboratory and characterized using scanning electron microscopy, X-ray diffraction, and Fourier transform infrared. To avoid the interference of other factors, all the treatments were divided into three groups: (i) blank treatment (no fertilizer), (ii) CF treatment, and (iii) combined [MNFf + CFs] treatment. The vegetative growth and qualitative and quantitative attributes of tomatoes were recorded, and the NUE, total production, and benefit–cost ratio (BCR) were also calculated. In addition, comparative nutritional properties for all treatments were analyzed. The plant’s height, stem diameter, root length, photosynthetic pigments, leaf minerals, and qualitative traits of tomato fruits were significantly (p < 0.05) increased by [MNFf + CFs] treatment compared to CFs. The protein, fiber, Fe, Zn, and K contents were significantly (p < 0.05) increased by 23.80, 38.10, 44.23, 60.01, and 2.39%, respectively, with the [MNFf + CFs] treatment as compared to CFs, while the ash and protein contents were both lower than the untreated tomato. Moreover, [MNFf + CFs] treatment has significantly (p < 0.05) increased the antioxidant properties. The NUE, total production, and BCR were also increased by 26.08, 26.04, and 25.38%, respectively, with the same treatment. Thus, [MNFf + CFs] treatment could be a potential alternative for reducing the excess use of CF.

Influence of bus stop land use characteristics on passenger waiting time satisfaction ‐ A case study in Guangzhou

Researchers usually conduct a questionnaire survey at bus stops to obtain data regarding the satisfaction of bus passengers with waiting times. The results are affected by many factors. Among them, the land use of the bus stops was proved to have an important impact on the survey results. The main contribution of this paper is the introduction of propensity score matching (PSM) into the evaluation of passenger waiting time satisfaction. By eliminating interference factors, this paper can quantify the impact of the various land use types of bus stops. On this basis, a method to modify the survey results of passenger waiting time satisfaction is proposed. This paper takes data pertaining to passenger satisfaction with bus service quality in Guangzhou City in 2018–2019 as an example, and the findings include that: different land use types of sites have different effects (positive or negative) on passenger waiting time scores. Also, matching propensity scores can balance the distribution of covariates between the treatment and control groups, effectively excluding the interference of other factors. After correcting the original rating results, this study found that 61.84% of the routes' waiting time ratings were overestimated. This finding indicates that data correction is necessary to accurately identify passenger waiting time ratings. The waiting time satisfaction of people using residential stations can best reflect the actual level. Therefore, it is suggested that stations with residential land use in each administrative area should be taken as representatives to conduct a waiting satisfaction survey.

How does China's carbon emissions trading (CET) policy affect the investment of CET-covered enterprises?

The carbon emissions trading (CET) policy realizes the internalization of emission reduction costs of related enterprises, which may affect their investment and management decisions, but has seldom received attention. Therefore, based on the panel data of A-share listed enterprises in eight energy-and‑carbon-intensive industries in China during 2009–2018, this paper employs the difference-in-differences (DID) and the difference-in-differences based propensity score matching methods (PSM-DID) to empirically evaluate the impact of China's CET policy on investment expenditure of CET-covered enterprises in seven pilot regions. The results indicate that: first of all, the investment expenditure of CET-covered enterprises has been reduced by 0.2449% due to China's CET policy during the sample period in general. Second, this impact shows significant industrial and regional heterogeneity. The CET policy reduces the investment expenditure of related enterprises in the building material and steel industries, but not in the other six industries. It also has a reducing impact on the investment expenditure of related enterprises in Beijing and Guangdong, but not in the other five pilot regions. Third, the impact began to appear in the second year of the implementation of CET policy, and it has shown an increasingly strengthening trend with continuous implementation. In addition, the central findings remain robust when we test the parallel trend assumption and apply the difference-in-differences-in-differences (DDD) method to further eliminate the interference of other factors.

Burden and Quality of Life of Family Caregivers of Stroke Patients

ABSTRACTThe purpose of this study was to identify the level of burden and quality of life of family caregivers of stroke patients and to investigate the correlation between burden, quality of life (including physical, social, psychological, and environmental domains), age of caregivers, and the care period. A descriptive correlational cross-sectional study was performed, with a convenience sample of family caregivers (n = 30) of stroke patients in São Paulo, Brazil. Data were collected using a questionnaire on participants’ characteristics, the Zarit Burden Interview Scale (ZBIS), and the World Health Organization Quality of Life-BREF (WHOQOL-BREF) instrument. A descriptive analysis was performed, and correlations between variables were analyzed using Pearson's product-moment correlation coefficient. The average burden score on the ZBIS was 29.6, representing a moderate burden, and the average overall quality of life score on the WHOQOL-BREF was 62.06%, which indicates moderate quality of life. A significant weak negative correlation was observed between burden and environmental domains (r = −0.470; p =.009), quality of life (r = −0.414; p =.023), and physical domains (r = −0.394; p =.031). No significant correlations were found between burden and quality of life, and variables in the psychological and social domains, age of caregivers, or care period. Caregivers for stroke patients presented with moderate levels of burden and reduction in quality of life. Levels of burden correlated negatively with environmental domains, quality of life levels, and physical domains; however, these correlations were weak, indicating the possible interference of other factors.

Dynamic accuracy evaluation for five-axis machine tools using S trajectory deviation based on R-test measurement

Abstract This paper presents a new S trajectory kinematic measurement method to evaluate the dynamic accuracy of five-axis machine tools based on R-test measurements. The S trajectory is obtained by scaling the machining path of the S-shaped test piece to the measuring stroke of the R-test. A geometric and dynamic accuracy simulation model is established to analyze the influence of various error factors on the S trajectory test and compare with the conical kinematic test described in ISO10791.6 quantitatively. The simulation results shown that the S trajectory test is more sensitive to most geometric errors and dynamic errors than the conical test. Particularly, to reflect the dynamic error factors such as poor rigidity of machine tools, servo mismatch, reverse error and nonlinear error, the S trajectory test has obvious advantages. Meanwhile, compared with the actual S-shaped piece machining, which is under development for inclusion in ISO 10791.7, the proposed non-cutting kinematic test method can simply reflect the dynamic accuracy of five axis machine tools itself without the interference of other factors and does not require additional workpiece and testing equipment. The proposed method is verified through experiments on a five-axis machine tool.

Prediction model of form error influenced by grinding wheel wear in grinding process of large-scale aspheric surface with SiC ceramics

Because of the material characteristic of high hardness and high abrasion resistance of SiC ceramics, grinding wheel wear is an essential problem which must be taken seriously and be solved in grinding process, especially in grinding of large-scale aspheric surface. In this paper, a ground aspheric surface form error model in large-scale aspheric surface grinding process of SiC ceramics is built without considering any other conditions but just radius wear of the grinding wheel. In this model, volume grinding ratio is employed to combine the wear volume of the grinding wheel and the removed volume of SiC ceramics. Experiments are conducted to corroborate the feasibility of the model, and the results reveal that the forecast error between the predicted value and the experimental value is less than 15 %. Considering the assumptions and interference of other factors, the form error model is acceptable.

Influence of ketamine on amino acid neurotransmitters secretion by nerve cells in vitro

In order to study the influence of amino acid neurotransmitters secreted by the nerve cells after ketamine treatment, the nerve cells were cultured in vitro to exclude the interference of other factors in vivo and treated with three different doses of ketamine (1, 3 and 5 µg/mL). Then, the concentration of neuronal amino acid neurotransmitters was examined at 0, 15, 30, 45, 60, 90, 120 min after treatment. The trends of each amino acid concentration after ketamine treatment were nearly the same among the different treatment doses. After 15 min of adapting time, ketamine decreased the excitatory amino acid glutamic acid and aspartic acid concentration, and increased the concentration of the inhibitory amino acid glycine. Their concentrations showed a tendency to return approximately to the original level after 120 min.

Optimum 3D Matrix Stiffness for Maintenance of Cancer Stem Cells Is Dependent on Tissue Origin of Cancer Cells.

IntroductionThe growth and expression of cancer stem cells (CSCs) depend on many factors in the tumor microenvironment. The objective of this work was to investigate the effect of cancer cells’ tissue origin on the optimum matrix stiffness for CSC growth and marker expression in a model polyethylene glycol diacrylate (PEGDA) hydrogel without the interference of other factors in the microenvironment.MethodsHuman MCF7 and MDA-MB-231 breast carcinoma, HCT116 colorectal and AGS gastric carcinoma, and U2OS osteosarcoma cells were used. The cells were encapsulated in PEGDA gels with compressive moduli in the 2-70 kPa range and optimized cell seeding density of 0.6x106 cells/mL. Micropatterning was used to optimize the growth of encapsulated cells with respect to average tumorsphere size. The CSC sub-population of the encapsulated cells was characterized by cell number, tumorsphere size and number density, and mRNA expression of CSC markers.ResultsThe optimum matrix stiffness for growth and marker expression of CSC sub-population of cancer cells was 5 kPa for breast MCF7 and MDA231, 25 kPa for colorectal HCT116 and gastric AGS, and 50 kPa for bone U2OS cells. Conjugation of a CD44 binding peptide to the gel stopped tumorsphere formation by cancer cells from different tissue origin. The expression of YAP/TAZ transcription factors by the encapsulated cancer cells was highest at the optimum stiffness indicating a link between the Hippo transducers and CSC growth. The optimum average tumorsphere size for CSC growth and marker expression was 50 μm.ConclusionThe marker expression results suggest that the CSC sub-population of cancer cells resides within a niche with optimum stiffness which depends on the cancer cells’ tissue origin.

Research on the Enterprise Finance and Capital Operation under the ERP Management Balance

After theoretical analysis of empirical research by channel turnover period index of working capital, by setting the implementation and the implementation of ERP in the two groups sample data to avoid the interference of other factors outside the ERP. Through the virtual variable set of empirical analysis of the influence of ERP is to the enterprise working capital management. By paired sample test, it found that after the implementation of ERP enterprise marketing channel in recent years increased turnover period instead of working capital. It is associated with the global economic crisis. Through regression analysis in recent years enterprises to implement ERP is not noticeable to enterprise's working capital management improvement effect. Investigate its reason is summarized as the unreasonable design of ERP implementation, management and the influence of the macro economic situation influence business decisions.

Abstract 251: Engineered matrix to study the effect of microenvironment on cancer stem cell maintenance.

Abstract Introduction: Tumors are highly heterogeneous. The heterogeneity of the tumor tissue is rooted in the existence of cancer stem cells (CSCs). Therefore, understanding the mechanism of CSC maintenance and its regulation by the microenvironment is critical to cancer prevention and treatment. Since cancer takes many years to grow, it is important to develop in vitro models to study the molecular basis of tumorigenesis and progression. 3D cell culture systems with biologic materials that support adhesion and growth of many cell types have emerged as another approach to cancer stem cell research. However, it is not possible to isolate individual factors in the microenvironment and the effect on cell response with naturally derived materials. In an effort to control the cell microenvironment, we have developed novel inert permissive gels with controlled physical, mechanical, and biological properties that support the maintenance of CSCs and tumorsphere formation. The objective of this work was to investigate the effect of matrix stiffness and a CD44 binding peptide, conjugated to the inert hydrogel matrix, on tumorsphere formation and CSC maintenance. Methods: Mouse 4T1 and human MCF7 breast cancer cells were encapsulated in the inert PEGDA gel with conjugation of CD44BP. Control groups included dissolved CD44BP and the gel conjugated with mutant CD44BP. Tumorsphere size and density, and expression of CSC markers were determined with incubation time in tumor CSC culture medium. Effect of CD44BP conjugation on breast CSC maintenance was compared with those gels conjugated with integrin binding RGD peptide (IBP) and fibronectin-derived heparin binding peptide (FHBP). For in vivo, cell encapsulated gels were inoculated in syngeneic Balb/C mice and tumor formation was determined with time. Results: The gel stiffness had a strong effect on tumorsphere formation and the effect was bimodal. Tumorsphere formation and expression of CSC markers by the encapsulated cells peaked after 8 days of incubation. 4T1 and MCF7 cells encapsulated in the gel with 5-kPa stiffness formed the largest and highest density of tumorspheres, and had highest expression of breast CSC markers CD44 and ABCG2. Conjugation of CD44 binding peptide to the inert gel inhibited breast tumorsphere formation in vitro and in vivo. The ability of the encapsulated cells to form tumorspheres in the peptide-conjugated gels correlated with the expression of CSC markers. Tumorsphere formation in vitro was enhanced by FHBP while it was abolished by IBP. Conclusion: The PEGDA hydrogel cell culture system provides a novel tool to investigate the individual effect of factors in the microenvironment on CSC maintenance without interference of other factors. This model system can be used to understand the effect of individual factors in the microenvironment on epithelial to mesenchymal transition (EMT) and tumorigenesis. Citation Format: Xiaoming Yang, Samaneh Kamali, Esmaiel Jabbari. Engineered matrix to study the effect of microenvironment on cancer stem cell maintenance. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 251. doi:10.1158/1538-7445.AM2013-251

Effect of CD44 Binding Peptide Conjugated to an Engineered Inert Matrix on Maintenance of Breast Cancer Stem Cells and Tumorsphere Formation

IntroductionAs cancer cells are affected by many factors in their microenvironment, a major challenge is to isolate the effect of a specific factor on cancer stem cells (CSCs) while keeping other factors unchanged. We have developed a synthetic inert 3D polyethylene glycol diacrylate (PEGDA) gel culture system as a unique tool to study the effect of microenvironmental factors on CSCs response. We have reported that CSCs formed in the inert PEGDA gel by encapsulation of breast cancer cells maintain their stemness within a certain range of gel stiffness. The objective was to investigate the effect of CD44 binding peptide (CD44BP) conjugated to the gel on the maintenance of breast CSCs.Methods4T1 or MCF7 breast cancer cells were encapsulated in PEGDA gel with CD44BP conjugation. Control groups included dissolved CD44BP and the gel with mutant CD44BP conjugation. Tumorsphere size and density, and expression of CSC markers were determined after 9 days. For in vivo, cell encapsulated gels were inoculated in syngeneic Balb/C mice and tumor formation was determined after 4 weeks. Effect of CD44BP conjugation on breast CSC maintenance was compared with integrin binding RGD peptide (IBP) and fibronectin-derived heparin binding peptide (FHBP).ResultsConjugation of CD44BP to the gel inhibited breast tumorsphere formation in vitro and in vivo. The ability of the encapsulated cells to form tumorspheres in the peptide-conjugated gels correlated with the expression of CSC markers. Tumorsphere formation in vitro was enhanced by FHBP while it was abolished by IBP.ConclusionCD44BP and IBP conjugated to the gel abolished tumorsphere formation by encapsulated 4T1 cells while FHBP enhanced tumorsphere formation compared to cells in the gel without peptide. The PEGDA hydrogel culture system provides a novel tool to investigate the individual effect of factors in the microenvironment on CSC maintenance without interference of other factors.