Differential Expression of Inflammarafts in Macrophage Foam Cells and in Nonfoamy Macrophages in Atherosclerotic Lesions-Brief Report.

BACKGROUND: Reprogramming of monocytes and macrophage manifests in hyperinflammatory responses and chronification of inflammation in atherosclerosis. Recent studies focused on epigenetic, transcriptional, and metabolic alterations that characterize trained immunity. However, the underlying effector mechanisms driving the hyperinflammatory response of reprogrammed macrophages remain unclear. We hypothesized that the plasma membrane of atherosclerotic lesion macrophages undergoes reprogramming to maintain inflammarafts, enlarged lipid rafts (LR) serving as a platform for assembly of inflammatory receptor complexes. METHODS: Single-cell suspensions from the aortae of Western diet-fed Ldlr-/- mice were gated for BODIPY-high foamy and BODIPY-low nonfoamy F4/80 macrophages by flow cytometry. Inflammarafts were characterized by increased levels of LR, TLR4 (toll-like receptor-4) localization to LR, TLR4 dimers, and the proximity between TLR2, TLR1, and CD36. In a cellular model of trained immunity, LR, TLR4 dimers, and the inflammatory response were measured in bone marrow-derived macrophages subjected to a 24-hour treatment with LPS (lipopolysaccharide) or OxLDL (oxidized low-density lipoprotein), followed by a 6-day wash-out period. RESULTS: Nonfoamy macrophages, which constituted ≈40% of macrophages in atherosclerotic lesions, expressed significantly higher levels of LR and TLR4 dimers, as well as proximity ligation signals for TLR4-LR, TLR2-CD36, and TLR2-TLR1 complexes, compared with foamy macrophages. These inflammaraft measures associated, to a different degree, with plasma cholesterol and inflammatory cytokines, as well as the size of the atherosclerotic lesions and necrotic cores. The bone marrow-derived macrophages trained with LPS simulated nonfoamy atherosclerotic lesion macrophages and continued to express inflammarafts and inflammatory genes for 6 days after LPS removal and displayed a hyperinflammatory response to Pam3CSK4, a TLR2/TLR1 agonist. OxLDL-exposed, lipid-laden macrophages did not express inflammarafts. CONCLUSIONS: Our data support the hypothesis that persistent inflammarafts in nonfoamy macrophages in atherosclerotic lesions serve as effectors of macrophage reprogramming into a hyperinflammatory phenotype.

Whole-tumor histogram analysis of postcontrast T1-weighted and apparent diffusion coefficient in predicting the grade and proliferative activity of adult intracranial ependymomas.

PURPOSE: To investigate the value of histogram analysis of postcontrast T1-weighted (T1C) and apparent diffusion coefficient (ADC) images in predicting the grade and proliferative activity of adult intracranial ependymomas. METHODS: Forty-seven adult intracranial ependymomas were enrolled and underwent histogram parameters extraction (including minimum, maximum, mean, 1st percentile (Perc.01), Perc.05, Perc.10, Perc.25, Perc.50, Perc.75, Perc.90, Perc.95, Perc.99, standard deviation (SD), variance, coefficient of variation (CV), skewness, kurtosis, and entropy of T1C and ADC) using FireVoxel software. Differences in histogram parameters between grade 2 and grade 3 adult intracranial ependymomas were compared. Receiver operating characteristic curves and logistic regression analyses were conducted to evaluate the diagnostic performance. Spearman's correlation analysis was used to evaluate the relationship between histogram parameters and Ki-67 proliferation index. RESULTS: Grade 3 intracranial ependymomas group showed significantly higher Perc.95, Perc.99, SD, variance, CV, and entropy of T1C; lower minimum, mean, Perc.01, Perc.05, Perc.10, Perc.25, Perc.50 of ADC; and higher CV and entropy of ADC than grade 2 intracranial ependymomas group (all p < 0.05). Entropy (T1C) and Perc.10 (ADC) had a higher diagnostic performance with AUCs of 0.805 and 0.827 among the histogram parameters of T1C and ADC, respectively. The diagnostic performance was improved by combining entropy (T1C) and Perc.10 (ADC), with an AUC of 0.857. Significant correlations were observed between significant histogram parameters of T1C (r = 0.296-0.417, p = 0.001-0.044) and ADC (r = -0.428-0.395, p = 0.003-0.038). CONCLUSION: Whole-tumor histogram analysis of T1C and ADC may be a promising approach for predicting the grade and proliferative activity of adult intracranial ependymomas.

NAT10/CEBPB/vimentin signalling axis promotes adenoid cystic carcinoma malignant phenotypes in vitro.

OBJECTIVE: To explore the biological function and mechanisms of CEBPB and NAT10-mediated N4-acetylcytidine (ac4c) modification in salivary adenoid cystic carcinoma (SACC). MATERIALS AND METHODS: CEBPB and NAT10 were knocked down in SACC-LM cells by siRNA transfection and overexpressed in SACC-83 cells by plasmid transfection. Malignant phenotypes were evaluated using CCK-8, Transwell migration and colony formation assays. Real-time PCR, western blotting, ChIP and acRIP were used to investigate the molecular mechanisms involved. RESULTS: We found that CEBPB was highly expressed in SACC tissues and correlated with lung metastasis and unfavourable prognosis. Gain- and loss-of-function experiments revealed that CEBPB promoted SACC malignant phenotypes. Mechanistically, CEBPB exerted its oncogenic effect by binding to the vimentin gene promoter region to enhance its expression. Moreover, NAT10-mediated ac4c modification led to stabilization and overexpression of CEBPB in SACC cells. We also found that NAT10, the only known human enzyme responsible for ac4C modification, promoted SACC cell migration, proliferation and colony formation. Moreover, CEBPB overexpression restored the inhibitory effect of NAT10 knockdown on malignant phenotypes. CONCLUSIONS: Our study reveals the critical role of the newly identified NAT10/CEBPB/vimentin axis in SACC malignant progression, and the findings may be applied to improve treatment for SACC.

Enhancing Camera Calibration for Traffic Surveillance with an Integrated Approach of Genetic Algorithm and Particle Swarm Optimization.

Recent advancements in sensor technologies, coupled with signal processing and machine learning, have enabled real-time traffic control systems to effectively adapt to changing traffic conditions. Cameras, as sensors, offer a cost-effective means to determine the number, location, type, and speed of vehicles, aiding decision-making at traffic intersections. However, the effective use of cameras for traffic surveillance requires proper calibration. This paper proposes a new optimization-based method for camera calibration. In this approach, initial calibration parameters are established using the Direct Linear Transformation (DLT) method. Then, optimization algorithms are applied to further refine the calibration parameters for the correction of nonlinear lens distortions. A significant enhancement in the optimization process is achieved through the integration of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) into a combined Integrated GA and PSO (IGAPSO) technique. The effectiveness of this method is demonstrated through the calibration of eleven roadside cameras at three different intersections. The experimental results show that when compared to the baseline DLT method, the vehicle localization error is reduced by 22.30% with GA, 22.31% with PSO, and 25.51% with IGAPSO.

Bacillus altitudinis AD13-4 Enhances Saline-Alkali Stress Tolerance of Alfalfa and Affects Composition of Rhizosphere Soil Microbial Community.

Saline and alkaline stresses limit plant growth and reduce crop yield. Soil salinization and alkalization seriously threaten the sustainable development of agriculture and the virtuous cycle of ecology. Biofertilizers made from plant growth-promoting rhizobacteria (PGPR) not only enhance plant growth and stress tolerance, but also are environmentally friendly and cost-effective. There have been many studies on the mechanisms underlying PGPRs enhancing plant salt resistance. However, there is limited knowledge about the interaction between PGPR and plants under alkaline-sodic stress. To clarify the mechanisms underlying PGPR's improvement of plants' tolerance to alkaline-sodic stress, we screened PGPR from the rhizosphere microorganisms of local plants growing in alkaline-sodic land and selected an efficient strain, Bacillus altitudinis AD13-4, as the research object. Our results indicate that the strain AD13-4 can produce various growth-promoting substances to regulate plant endogenous hormone levels, cell division and differentiation, photosynthesis, antioxidant capacity, etc. Transcriptome analysis revealed that the strain AD13-4 significantly affected metabolism and secondary metabolism, signal transduction, photosynthesis, redox processes, and plant-pathogen interactions. Under alkaline-sodic conditions, inoculation of the strain AD13-4 significantly improved plant biomass and the contents of metabolites (e.g., soluble proteins and sugars) as well as secondary metabolites (e.g., phenols, flavonoids, and terpenoids). The 16S rRNA gene sequencing results indicated that the strain AD13-4 significantly affected the abundance and composition of the rhizospheric microbiota and improved soil activities and physiochemical properties. Our study provides theoretical support for the optimization of saline-alkali-tolerant PGPR and valuable information for elucidating the mechanism of plant alkaline-sodic tolerance.

Macrophage inflammarafts in atherosclerosis.

PURPOSE OF REVIEW: Advances in single cell techniques revealed a remarkable diversity in macrophage gene expression profiles in atherosclerosis. However, the diversity of functional processes at the macrophage plasma membrane remains less studied. This review summarizes recent advances in characterization of lipid rafts, where inflammatory receptors assemble, in macrophages that undergo reprogramming in atherosclerotic lesions and in vitro under conditions relevant to the development of atherosclerosis. RECENT FINDINGS: The term inflammarafts refers to enlarged lipid rafts with increased cholesterol content, hosting components of inflammatory receptor complexes assembled in close proximity, including TLR4-TLR4, TLR2-TLR1 and TLR2-CD36 dimers. Macrophages decorated with inflammarafts maintain chronic inflammatory gene expression and are primed to an augmented response to additional inflammatory stimuli. In mouse atherosclerotic lesions, inflammarafts are expressed primarily in nonfoamy macrophages and less in lipid-laden foam cells. This agrees with the reported suppression of inflammatory programs in foam cells. In contrast, nonfoamy macrophages expressing inflammarafts are the major inflammatory population in atherosclerotic lesions. Discussed are emerging reports that help understand formation and persistence of inflammarafts and the potential of inflammarafts as a novel therapeutic target. SUMMARY: Chronic maintenance of inflammarafts in nonfoamy macrophages serves as an effector mechanism of inflammatory macrophage reprogramming in atherosclerosis.

Individual Micron-Sized Aerosol Qualitative Analysis-Combined Raman Spectroscopy and Laser-Induced Breakdown Spectroscopy by Optical Trapping in Air.

The attribution of single particle sources of atmospheric aerosols is an essential problem in the study of air pollution. However, it is still difficult to qualitatively analyze the source of a single aerosol particle using noncontact in situ techniques. Hence, we proposed using optical trapping to combine gated Raman spectroscopy with laser-induced breakdown spectroscopy (LIBS) in a single levitated micron aerosol. The findings of the spectroscopic imaging indicated that the particle plasma formed by a single particle ablation with a pulsed laser within 7 ns deviates from the trapped particle location. The LIBS acquisition field of view was expanded using the 19-bundle fiber, which also reduces the fluctuation of a single particle signal. In addition, gated Raman was utilized to suppress the fluorescence and increase the Raman signal-to-noise ratio. Based on this, Raman can measure hard-to-ionize substances with LIBS, such as sulfates. The LIBS radical can overcome the restriction that Raman cannot detect ionic chemicals like fluoride and chloride in halogens. To test the capability of directly identifying distinctive feature compounds utilizing spectra, we detected anions using Raman spectroscopy and cations using LIBS. Four typical mineral aerosols are subjected to precise qualitative evaluations (marble, gypsum, baking soda, and activated carbon adsorbed potassium bicarbonate). To further validate the application potential for substances with indistinctive feature discrimination, we employed machine learning algorithms to conduct a qualitative analysis of the coal aerosol from ten different origin regions. Three data fusion methodologies (early fusion, intermediate fusion, and late fusion) for Raman and LIBS are implemented, respectively. The accuracy of the late fusion model prediction using StackingClassifier is higher than that of the LIBS data (66.7%) and Raman data (86.1%) models, with an average accuracy of 90.6%. This research has the potential to provide online single aerosol analysis as well as technical assistance for aerosol monitoring and early warning.

Development of an MRI-Based Comprehensive Model Fusing Clinical, Radiomics and Deep Learning Models for Preoperative Histological Stratification in Intracranial Solitary Fibrous Tumor.

BACKGROUND: Accurate preoperative histological stratification (HS) of intracranial solitary fibrous tumors (ISFTs) can help predict patient outcomes and develop personalized treatment plans. However, the role of a comprehensive model based on clinical, radiomics and deep learning (CRDL) features in preoperative HS of ISFT remains unclear. PURPOSE: To investigate the feasibility of a CRDL model based on magnetic resonance imaging (MRI) in preoperative HS in ISFT. STUDY TYPE: Retrospective. POPULATION: Three hundred and ninety-eight patients from Beijing Tiantan Hospital, Capital Medical University (primary training cohort) and 49 patients from Lanzhou University Second Hospital (external validation cohort) with ISFT based on histopathological findings (237 World Health Organization [WHO] tumor grade 1 or 2, and 210 WHO tumor grade 3). FIELD STRENGTH/SEQUENCE: 3.0 T/T1-weighted imaging (T1) by using spin echo sequence, T2-weighted imaging (T2) by using fast spin echo sequence, and T1-weighted contrast-enhanced imaging (T1C) by using two-dimensional fast spin echo sequence. ASSESSMENT: Area under the receiver operating characteristic curve (AUC) was used to assess the performance of the CRDL model and a clinical model (CM) in preoperative HS in the external validation cohort. The decision curve analysis (DCA) was used to evaluate the clinical net benefit provided by the CRDL model. STATISTICAL TESTS: Cohen's kappa, intra-/inter-class correlation coefficients (ICCs), Chi-square test, Fisher's exact test, Student's t-test, AUC, DCA, calibration curves, DeLong test. A P value <0.05 was considered statistically significant. RESULTS: The CRDL model had significantly better discrimination ability than the CM (AUC [95% confidence interval, CI]: 0.895 [0.807-0.912] vs. 0.810 [0.745-0.874], respectively) in the external validation cohort. The CRDL model can provide a clinical net benefit for preoperative HS at a threshold probability >20%. DATA CONCLUSION: The proposed CRDL model holds promise for preoperative HS in ISFT, which is important for predicting patient outcomes and developing personalized treatment plans. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Facile Approach to Fabricate Oriented Porous PDMS Composites for Movements Monitoring and Identifying Motion Patterns.

The facile and rapid fabrication of oriented porous polymers is crucial for flexible pressure sensors. Herein, a pressure sensor is developed based on oriented porous polydimethylsiloxane (PDMS) composites for detecting human motion and identifying joint motion patterns. The oriented porous PDMS composite is first constructed through thiol-ene click chemistry and directional freezing within only 30 min, then fabricated by interfacial in situ polymerization of dopamine and pyrrole to generate robust interfaces. As a result, the as-prepared oriented porous PDMS composite is assembled into a pressure sensor that shows potential applications in pressure and human motion detection. Interestingly, a sensor assembled by orthogonally stacking the PDMS composites can be used for joint motion pattern recognition with potential monitoring of football motion due to their directional structures. This facile strategy coupled with the oriented porous structure is expected to help design advanced wearable electronic devices.

Long non-coding RNA MRPL23-AS1 suppresses anoikis in salivary adenoid cystic carcinoma in vitro.

Distant lung metastasis is the main factor that affects the survival rate of patients with salivary adenoid cystic carcinoma (SACC). Anoikis resistance is a feature of tumor cells that easily metastasize. The long non-coding RNA (lncRNA) MRPL23 antisense RNA 1 (MPRL23-AS1) is related to lung metastasis in SACC, but its role in anoikis resistance is unknown. After altering MPRL23-AS1 expression in SACC cells, anoikis resistance was detected by calcein AM/PI staining and annexin V/PI flow cytometry. The apoptosis marker activated caspase-3 and the bcl-2/bax ratio were detected by Western blotting. The relationship between MPRL23-AS1 and the promoter of the potential downstream target gene p19INK4D was identified by chromatin immunoprecipitation (ChIP)-PCR assay. p19INK4D expression in patient tissues was determined using qRT-PCR and immunohistochemistry. The functional experiments showed that MPRL23-AS1 could promote anoikis resistance in vitro. MRPL23-AS1 recruited the EZH2 to the promoter region of p19INK4D, inhibited p19INK4D expression, and promoted tumor cell anoikis resistance. p19INK4D overexpression did not affect anoikis in attached cells; however, it attenuated the anoikis resistance effect of MPRL23-AS1 in suspension cells. p19INK4D expression was significantly lower in SACC tissues than in normal tissues. The novel MRPL23-AS1/p19INK4D axis may be a potential SACC biomarker or therapeutic target.

Postoperative progression of intracranial grade II-III solitary fibrous tumor/hemangiopericytoma: predictive value of preoperative magnetic resonance imaging semantic features.

BACKGROUND: Preoperative prediction of postoperative tumor progression of intracranial grade II-III hemangiopericytoma is the basis for clinical treatment decisions. PURPOSE: To use preoperative magnetic resonance imaging (MRI) semantic features for predicting postoperative tumor progression in patients with intracranial grade II-III solitary fibrous tumor/hemangiopericytoma (SFT/HPC). MATERIAL AND METHODS: We retrospectively analyzed the preoperative MRI data of 42 patients with intracranial grade II-III SFT/HPC, as confirmed by surgical resection and pathology in our hospital from October 2010 to October 2017, who were followed up for evaluation of recurrence, metastasis, or death. We applied strict inclusion and exclusion criteria and finally included 37 patients. The follow-up time was in the range of 8-120 months (mean = 57.1 months). RESULTS: Single-factor survival analysis revealed that tumor grade (log-rank, P = 0.024), broad-based tumor attachment to the dura mater (log-rank, P = 0.009), a blurred tumor-brain interface (log-rank, P = 0.008), skull invasion (log-rank, P = 0.002), and the absence of postoperative radiotherapy (log-rank, P = 0.006) predicted postoperative intracranial SFT/HPC progression. Multivariate survival analysis revealed that tumor grade (P = 0.009; hazard ratio [HR] = 11.42; 95% confidence interval [CI] = 1.832-71.150), skull invasion (P = 0.014; HR = 5.72; 95% CI = 1.421-22.984), and the absence of postoperative radiotherapy (P = 0.001; HR = 0.05; 95% CI = 0.008-0.315) were independent predictors of postoperative intracranial SFT/HPC progression. CONCLUSION: Broad-based tumor attachment to the dura mater, skull invasion, and blurring of the tumor-brain interface can predict postoperative intracranial SFT/HPC progression.

Sensor Fusion-Based Vehicle Detection and Tracking Using a Single Camera and Radar at a Traffic Intersection.

Recent advancements in sensor technologies, in conjunction with signal processing and machine learning, have enabled real-time traffic control systems to adapt to varying traffic conditions. This paper introduces a new sensor fusion approach that combines data from a single camera and radar to achieve cost-effective and efficient vehicle detection and tracking. Initially, vehicles are independently detected and classified using the camera and radar. Then, the constant-velocity model within a Kalman filter is employed to predict vehicle locations, while the Hungarian algorithm is used to associate these predictions with sensor measurements. Finally, vehicle tracking is accomplished by merging kinematic information from predictions and measurements through the Kalman filter. A case study conducted at an intersection demonstrates the effectiveness of the proposed sensor fusion method for traffic detection and tracking, including performance comparisons with individual sensors.

Vehicle Localization in 3D World Coordinates Using Single Camera at Traffic Intersection.

Optimizing traffic control systems at traffic intersections can reduce the network-wide fuel consumption, as well as emissions of conventional fuel-powered vehicles. While traffic signals have been controlled based on predetermined schedules, various adaptive signal control systems have recently been developed using advanced sensors such as cameras, radars, and LiDARs. Among these sensors, cameras can provide a cost-effective way to determine the number, location, type, and speed of the vehicles for better-informed decision-making at traffic intersections. In this research, a new approach for accurately determining vehicle locations near traffic intersections using a single camera is presented. For that purpose, a well-known object detection algorithm called YOLO is used to determine vehicle locations in video images captured by a traffic camera. YOLO draws a bounding box around each detected vehicle, and the vehicle location in the image coordinates is converted to the world coordinates using camera calibration data. During this process, a significant error between the center of a vehicle's bounding box and the real center of the vehicle in the world coordinates is generated due to the angled view of the vehicles by a camera installed on a traffic light pole. As a means of mitigating this vehicle localization error, two different types of regression models are trained and applied to the centers of the bounding boxes of the camera-detected vehicles. The accuracy of the proposed approach is validated using both static camera images and live-streamed traffic video. Based on the improved vehicle localization, it is expected that more accurate traffic signal control can be made to improve the overall network-wide energy efficiency and traffic flow at traffic intersections.

Advances in computed tomography-based prognostic methods for intracerebral hemorrhage.

Spontaneous intracerebral hemorrhage (ICH) has high morbidity and mortality. Computed tomography (CT) plays an important role in the diagnosis, treatment, and research of cerebrovascular diseases. Non-contrast CT is widely used in the clinical diagnosis of ICH because of its high imaging speed and high sensitivity and specificity in the detection of stroke. Many markers-based CT imaging, quantitative parameters, and artificial intelligence (AI) methods based on CT are increasingly used for the prediction of hematoma expansion (HE), prognosis of ICH, and the evaluation of perihematomal edema (PHE). Therefore, we performed a comprehensive review of studies, focusing on current research evidence related to CT use for the prediction of HE and prognostic. This review discusses recent insights into, outlines current limitations, and puts forward suggestions for the challenges and directions of future research. Although at present the prognosis for ICH is not optimistic, the treatment methods remain controversial. However, identifying imaging markers that can evaluate and predict existing possible existing therapeutic targets could help to provide individualized advice for patients and achieve patient risk stratification, which is a key step in improving treatment outcomes.

The relationship between the apparent diffusion coefficient and the Ki-67 proliferation index in intracranial solitary fibrous tumor/hemangiopericytoma.

This study evaluated the value of the apparent diffusion coefficient (ADC) in distinguishing grade II and III intracranial solitary fibrous tumors/hemangiopericytomas and explored the correlation between ADC and Ki-67. The preoperative MRIs of 37 patients treated for solitary fibrous tumor/hemangiopericytoma (grade II, n = 15 and grade III, n = 22) in our hospital from 2011 to October 2020 were retrospectively analyzed. We compared the difference between the minimum, average, maximum, and relative ADCs based on tumor grade and examined the correlation between ADC and Ki-67. Receiver operating characteristic curve analysis was used to analyze the diagnostic efficiency of the ADC. There were significant differences in the average, minimum, and relative ADCs between grade II and III patients. The optimal cutoff value for the relative ADC value to differentiate grade II and III tumors was 0.998, which yielded an area under the curve of 0.879. The Ki-67 proliferation indexes of grade II and III tumors were significantly different, and the average (r = - 0.427), minimum (r = - 0.356), and relative (r = - 0.529) ADCs were significantly negatively correlated with the Ki-67 proliferation index. ADC can be used to differentiate grade II and III intracranial solitary fibrous tumors/hemangiopericytomas. Our results can be used to formulate a personalized surgical treatment plan before surgery.

Differentiation of intracranial solitary fibrous tumor/hemangiopericytoma from atypical meningioma using apparent diffusion coefficient histogram analysis.

This study aimed to investigate the value of apparent diffusion coefficient (ADC) histogram analysis in differentiating intracranial solitary fibrous tumor/hemangiopericytoma (SFT/HPC) from atypical meningioma (ATM). Retrospective analyzed the clinical, magnetic resonance imaging, and pathological data of 20 and 25 patients with SFT/HPC and ATM, respectively. Histogram analysis was performed on the axial ADC images using MaZda software, and nine histogram parameters were obtained, including mean, variance, skewness, kurtosis, and the 1st (ADC1), 10th (ADC10), 50th (ADC50), 90th (ADC90), and 99th (ADC99) percentile ADC. Differences in ADC histogram parameters between SFT/HPC and ATM were compared by an independent t test or Mann-Whitney U test, while the statistically significant histogram parameters were further analyzed by drawing receiver operating characteristic (ROC) curves to evaluate the differential diagnostic performance. Among the nine ADC histogram parameters we extracted, the mean, ADC1, ADC10, ADC50, and ADC90 in the SFT/HPC group were greater than those of ATM, and significant differences were observed (all P < 0.05). ROC analysis showed that the ADC1 generated the highest area under the curve (AUC) value of 0.920 in distinguishing the two tumors, when using 91.00 as the optimal threshold. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value in distinguishing between SFT/HPC and ATM were 84.00%, 85.00%, 84.44%, 87.50%, and 81.00%, respectively. ADC histogram analysis can be a reliable tool to differentiate between SFT/HPC and ATM, with the ADC1 being the most promising potential parameter.

Study of Texture Indicators Applied to Pavement Wear Analysis Based on 3D Image Technology.

Pavement texture characteristics can reflect early performance decay, skid resistance, and other information. However, most statistical texture indicators cannot express this difference. This study adopts 3D image camera equipment to collect texture data from laboratory asphalt mixture specimens and actual pavement. A pre-processing method was carried out, including data standardisation, slope correction, missing value and outlier processing, and envelope processing. Then the texture data were calculated based on texture separation, texture power spectrum, grey level co-occurrence matrix, and fractal theory to acquire six leading texture indicators and eight extended indicators. The Pearson correlation coefficient was used to analyse the correlation of different texture indicators. The distinction vector based on the information entropy is calculated to analyse the distinction of the indicators. High correlations between ENE (energy) and ENT (entropy), ENT and D (Minkowski dimension) were found. The CON (contrast) has low correlations with HT (macro-texture power spectrum area), ENT and D. However, the differentiation of ENE and HT is more prominent, and the differentiation of the CON is smaller. ENE, ENT, CON and D indicators based on macro-texture and the corresponding original texture have strong linear correlations. However, the microtexture indicators are not linearly correlated with the corresponding original texture indicators. D, WT (micro-texture power spectrum area) and ENT exhibit high degrees of numerical concentration for the same road sections and may be more statistically helpful in distinguishing the characteristics of the pavement performance decay of the road sections.

Dimethyl phthalate damages Staphylococcus aureus by changing the cell structure, inducing oxidative stress and inhibiting energy metabolism.

Dimethyl phthalate (DMP), used as a plasticizer in industrial products, exists widely in air, water and soil. Staphylococcus aureus is a typical model organism representing Gram-positive bacteria. The molecular mechanisms of DMP toxicology in S. aureus were researched by proteomic and transcriptomic analyses. The results showed that the cell wall, membrane and cell surface characteristics were damaged and the growth was inhibited in S. aureus by DMP. Oxidative stress was induced by DMP in S. aureus. The activities of succinic dehydrogenase (SDH) and ATPase were changed by DMP, which could impact energy metabolism. Based on proteomic and transcriptomic analyses, the oxidative phosphorylation pathway was enhanced and the glycolysis/gluconeogenesis and pentose phosphate pathways were inhibited in S. aureus exposed to DMP. The results of real-time reverse transcription quantitative PCR (RT-qPCR) further confirmed the results of the proteomic and transcriptomic analyses. Lactic acid, pyruvic acid and glucose were reduced by DMP in S. aureus, which suggested that DMP could inhibit energy metabolism. The results indicated that DMP damaged the cell wall and membrane, induced oxidative stress, and inhibited energy metabolism and activation in S. aureus.

Bacillus pumilus LZP02 Promotes Rice Root Growth by Improving Carbohydrate Metabolism and Phenylpropanoid Biosynthesis.

Elucidation of the underlying mechanisms of plant growth promotion of rhizobacteria is very important. This study explored the mechanism by which Bacillus pumilus LZP02 promotes growth in rice roots through proteomic, transcriptomic, and metabolomic techniques. The results showed that B. pumilus LZP02 promoted the absorption of phosphorous, calcium, and magnesium ions by colonization of rice roots and enhanced peroxidase, catalase, superoxide dismutase, and Ca2+Mg2+ adenosine triphosphatase activities and chlorophyll contents in rice. The proteomic results showed that most of the differentially expressed proteins were involved in carbohydrate metabolism and that the biosynthesis of other secondary metabolites was also increased. According to RNA-seq and reverse transcription-quantitative PCR analyses, expression of some genes involved in carbohydrate metabolism and phenylpropanoid biosynthesis was upregulated in rice roots. Regarding metabolomics, phenylpropanoid biosynthesis, starch and sucrose metabolism, the pentose phosphate pathway, and glyoxylate and dicarboxylate metabolism were increased. The results indicated that B. pumilus LZP02 promoted the growth of rice roots by enhancing carbohydrate metabolism and phenylpropanoid biosynthesis.

A Location Privacy Attack Based on the Location Sharing Mechanism with Erroneous Distance in Geosocial Networks.

Geographical social networks (GSN) is an emerging research area. For example, Foursquare, Yelp, and WeChat are all well-known service providers in this field. These applications are also known as location-based services (LBS). Previous studies have suggested that these location-based services may expose user location information. In order to ensure the privacy of the user's location data, the service provider may provide corresponding protection mechanisms for its applications, including spatial cloaking, fuzzy location information, etc., so that the user's real location cannot be easily cracked. It has been shown that if the positioning data provided by the user is not accurate enough, it is still difficult for an attacker to obtain the user's true location. Taking this factor into consideration, our attack method is divided into two stages for the entire attack process: (1) Search stage: cover the area where the targeted user is located with unit discs, and then calculate the minimum dominating set. Use the triangle positioning method to find the minimum precision disc. (2) Inference phase: Considering the existence of errors, an Error-Adjusted Space Partition Attack Algorithm (EASPAA) was proposed during the inference phase. Improved the need for accurate distance information to be able to derive the user's true location. In this study, we focus on the Location Sharing Mechanism with Maximal Coverage Limit to implement the whole attack. Experimental results show that the proposed method still can accurately infer the user's real location even when there is an error in the user's location information.