The improvement of Coreopsis tinctoria essential oil on learning and memory impairment of d-galactose-induced mice through Nrf2/NF-κB pathway

Essential oil of Coreopsis tinctoria (EOC) is a essential substance extracted from Coreopsis tinctoria with the excellent anti-oxidant effect. However, it is still unclear whether EOC can improve learning and memory impairment and its mechanism. The purpose of this study was to investigate the effect of EOC on learning and memory impairment induced by D-galactose (D-gal) in mice and reveal its mechanism. The composition of EOC was analyzed by GC-MS, and the results showed that the highest content was D-limonene. The follow-up experiments were conducted by comparing EOC with D-limonene. The aging model was established by subcutaneous injection of D-gal, and donepezil, D-limonene and EOC were given by intragastric administration. It was found that EOC and D-limonene significantly improved learning and memory impairment induced by D-gal through the Morris water maze and step-through tests. Pathological and biochemical analysis showed that the hippocampal morphologic of mice was damage and the activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) induced by D-gal were decreased, while the content of malondialdehyde (MDA) was increased, while EOC and D-limonene could reverse the morphological changes and reduce oxidative damage. In addition, EOC and D-limonene significantly increased body weight and organ coefficients, including liver, spleen and kidney. Moreover, EOC and D-limonene improved the expression of nuclear factor E2 related factor 2 (Nrf2) pathway and inhibited nuclear transcription factors-κB (NF-κB) pathway. In summary, the results showed that EOC and D-limonene could improve learning and memory impairment induced by D-gal through Nrf2/ NF-κB pathway. It was clear that as a mixture, EOC was better than D-limonene on improving learning and memory impairment.

Generalized Cross-Correlation Strain Demodulation Method Based on Local Similar Spectral Scanning

Optical fiber measurement technology is widely used in the strength testing of buildings, the health testing of industrial equipment, and the minimally invasive surgery of modern medical treatment due to its characteristics of free calibration, high precision, and small size. This paper presents an algorithm that can improve the range and stability of strain measurements in order to solve the problems of the small range and measurement failure of optical fiber strain sensors based on optical frequency-domain reflectometry (OFDR). Firstly, a Rayleigh scattering model based on the refractive index perturbation of an optical fiber is proposed to study the characteristics of Rayleigh scattering and to guide the strain demodulation algorithm based on the spectral shift. Secondly, a local similar scanning method that can maintain a high similarity by monitoring local Rayleigh scattering signals (LSs) before and after strain is proposed. Thirdly, a generalized cross-correlation algorithm is proposed to detect spectral offset, solving the problem of demodulation failure in the case of a Rayleigh scattering signal with a low signal-to-noise ratio. Experiments show that the proposed method still has high stability when the spatial resolution is 3 mm. The measurement precision is 6.2 με, which proves that the multi-peaks or pseudo-peaks of the traditional algorithm in the case of a large strain, the high spatial resolution, and the poor signal-to-noise ratio are solved, and the stability of the strain measurement process is improved.

[The preference for Front-of-Pack Labeling and its association with the understanding of Nutrition Facts Panel among residents aged 18 to 70: results of a survey in 6 provinces of China]

Objective: To investigate the preference for Front-of-Pack Labeling (FOP) and its association with the understanding of the Nutrition Facts Panel among Chinese residents. Methods: A multi-stage sampling strategy was adopted to select 3 002 people aged between 18 and 70 years old from the eastern region of China (Beijing, Jiangsu Province, Guangdong Province), the northeast region (Heilongjiang Province), the central region (Henan Province) and the western region (Sichuan Province) from July 2020 to March 2021. Socio-demographic characteristics of participants and their understanding of the Nutrition Facts Panel and preference for FOP were collected. The χ² test was conducted to compare the preference for FOP in different groups of population, and multivariate logistic regression was used to analyze the association between the preference for FOP and the understanding of the Nutrition Facts Panel. Results: The mean age of 3 002 participants was (42.3±13.4) years, of which 1 914 (63.8%) were females and 69.3% could not understand the Nutrition Facts Panel. About 2 458 respondents (81.9%) suggested that FOP could be promoted. The top three nutrients that should be labeled were sugar (68.4%), salt (68.2%) and total fat (62.4%). The number of participants who believed that the Multiple Traffic Lights (MTL) could be easier to help consumers to quickly choose healthy food, attract attention and provide the most needed information was 1 064 (35.4%), 1 026 (34.2%) and 1 140 (38.0%), respectively. The multivariate logistic regression analysis showed that, compared with the Guideline Daily Amount (GDA) system, participants who could not understand the Nutrition Facts Panel preferred (1) Nutri-Score, Warning labels, and Health logos: Smart Choice in terms of"Which format of FOP could quickly help you choose food more easily?"[OR (95%CI): 2.21 (1.62-3.02), 1.64 (1.22-2.22), 1.79 (1.31-2.45), respectively]; (2) Nutri-Score, Warning labels, and Health logos: Smart Choice in terms of"Which format of FOP could attract your attention the most?"[OR (95%CI): 2.62 (1.92-3.59), 1.96 (1.45-2.66), 2.25 (1.66-3.04), respectively]; and (3) Nutri-Score, Warning labels, and Health logos: Smart Choice in terms of"Which format of FOP could provide you with the most needed information?"[OR (95%CI): 2.33 (1.70-3.21), 2.21 (1.66-2.95), 2.01 (1.50-2.71), respectively]. Conclusion: The residents from six provinces in China have a supportive attitude towards FOP. The interpretive FOP with color information, specific nutrient information and summary indicator can be launched. The nutrition information of sugar, salt and total fat could be prioritized to be labeled on the FOP.

Interferometric laser imaging for droplet-size measurement in spray

An upgraded droplet-size measurement method, based on laser interference particle imaging (IPI) technology, is applied to accomplish high-precision measurement of particle size and spatial distribution of gas-liquid two-phase flow in the atomization field. In this study, an improved morphological-Hough transform interference fringe location algorithm is applied to IPI measurement. The particle size of the standard particle field with a diameter of 24 µm is measured by the upgraded IPI measurement experimentally, whose absolute error and relative error are 0.14 µm and 0.58%, respectively. The atomization field of the 400 µm centrifugal nozzle under different pressures is demonstrated by direct imaging and IPI technology, where the assessment results are evaluated by SMD value and particle size distribution, and the results exhibit good agreement.

Precision roll angle measurement system based on autocollimation

The traditional autocollimation method is widely used for small angle measurement due to its high precision and high resolution, but it cannot be used to measure the roll angle. To overcome this problem, a roll angle measurement method based on autocollimation is proposed in this paper. To achieve roll angle measurement, a transmission grating is selected to generate a pair of measurement beams, and a combined target is designed as the angle sensor. A roll angle with higher accuracy and resolution can be obtained by differential measurement, because the measurement error introduced by the beam angle drift of the light source can be effectively suppressed. A series of experiments is carried out to verify the performance of the proposed system. In the experiments, the resolution of the roll angle is better than 0.05 arcsec, and the accuracy of the system is 0.20 arcsec with a measurement range of 250 arcsec.

A three-dimensional small angle measurement system based on autocollimation method

A laser autocollimator based on transmission grating and combined reflector is proposed to simultaneously measure a three-dimensional angle. The optical configuration of the proposed autocollimator is designed, and a mathematical model for measuring a three-dimensional angle is established. The three-dimensional angle is obtained by detecting the change in the direction of the three measurement beams generated by grating diffraction and reflected by a combined reflector. The experimental setup based on the proposed autocollimator was constructed, and a series of experiments were performed to verify the feasibility of the proposed autocollimator for precision angle measurement. The experimental results showed that the measurement resolution of three-dimensional angles is better than 0.01", with measurement repeatability of yaw, pitch, and roll angles being 0.013", 0.012", and 0.009", respectively.

Machine Learning in Differentiating Gliomas from Primary CNS Lymphomas: A Systematic Review, Reporting Quality, and Risk of Bias Assessment

BACKGROUND

Differentiating gliomas and primary CNS lymphoma represents a diagnostic challenge with important therapeutic ramifications. Biopsy is the preferred method of diagnosis, while MR imaging in conjunction with machine learning has shown promising results in differentiating these tumors.

PURPOSE

Our aim was to evaluate the quality of reporting and risk of bias, assess data bases with which the machine learning classification algorithms were developed, the algorithms themselves, and their performance.

DATA SOURCES

Ovid EMBASE, Ovid MEDLINE, Cochrane Central Register of Controlled Trials, and the Web of Science Core Collection were searched according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

STUDY SELECTION

From 11,727 studies, 23 peer-reviewed studies used machine learning to differentiate primary CNS lymphoma from gliomas in 2276 patients.

DATA ANALYSIS

Characteristics of data sets and machine learning algorithms were extracted. A meta-analysis on a subset of studies was performed. Reporting quality and risk of bias were assessed using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) and Prediction Model Study Risk Of Bias Assessment Tool.

DATA SYNTHESIS

The highest area under the receiver operating characteristic curve (0.961) and accuracy (91.2%) in external validation were achieved by logistic regression and support vector machines models using conventional radiomic features. Meta-analysis of machine learning classifiers using these features yielded a mean area under the receiver operating characteristic curve of 0.944 (95% CI, 0.898-0.99). The median TRIPOD score was 51.7%. The risk of bias was high for 16 studies.

LIMITATIONS

Exclusion of abstracts decreased the sensitivity in evaluating all published studies. Meta-analysis had high heterogeneity.

CONCLUSIONS

Machine learning-based methods of differentiating primary CNS lymphoma from gliomas have shown great potential, but most studies lack large, balanced data sets and external validation. Assessment of the studies identified multiple deficiencies in reporting quality and risk of bias. These factors reduce the generalizability and reproducibility of the findings.

[Contrastive analysis about the postoperative clinical characteristics of elderly patients with colorectal cancer in different age groups]

Objective: To explore the postoperative clinical characteristics of elderly patients with colorectal cancer at different ages. Methods: Retrospective analysis was performed on the clinical data of 720 elderly patients with Colorectal Cancer in Beijing Hospitals from January 2012 to December 2019. There were 411 males and 309 females with a median age of 74 years. We divided the patients into young-old, old-old, oldest-old colorectal cancer patient groups and used chi-square comparative analysis of different groups of patients with clinical disease characteristics. Results: The oldest-old colorectal cancer patients tended to have normal body mass index (BMI), and the site of the disease shifted to the right. The incidence of concomitant diseases such as heart disease and hypertension increases gradually with age, and the incidence of diabetes is highest in old-old colorectal cancer patients. The proportion of open surgery was higher in the oldest-old group, but the operation time was shorter than the other two groups. In addition, the incidence of postoperative complications in elderly patients with colorectal cancer gradually increases with age, especially cardiac complications and other complications such as pneumonia, deep venous thrombosis of lower limbs, urinary retention, urinary tract infection, renal failure, cerebral hemorrhage, cerebral infarction, and so on. Conclusions: The BMI of the oldest-old patients tended to be normal, and the site of the disease shifted to the right. The incidence of heart disease, hypertension, and other concomitant diseases and postoperative complications in elderly patients with colorectal cancer gradually increase with age. Thus, the choice of treatment should be more individualized for elderly patients with colorectal cancer, and more attention should be paid to perioperative management.

Effect of high soil C/N ratio and nitrogen limitation caused by the long-term combined organic-inorganic fertilization on the soil microbial community structure and its dominated SOC decomposition

The application of organic fertilizers, such as straw and manure, is an efficient approach to maintain soil productivity. However, the effect of these organic fertilizers on soil microbial nutrient balance has not yet been established. In this study, the effects of the long-term combined organic-inorganic fertilization on microbial community were investigated by conducting a 30-year-long field test. Overall, the following five fertilizer groups were employed: inorganic NP fertilizer (NP), inorganic NK fertilizer (NK), inorganic NPK fertilizer (NPK), NPK + manure (MNPK), and NPK + straw (SNPK). The results indicated that the mean natural logarithm of the soil C:N:P acquisition enzyme ratio was 1.04:1.11:1.00 under organic-inorganic treatments, which showed a deviation from its overall mean ratio of 1:1:1. This indicates that microbial resources do not have a balance. Vector analysis (vector angle <45°) and threshold elemental ratio analysis (R_C:N-TER_C:N > 0) further demonstrated that the microbial metabolism was limited by Nitrogen (N) under SNPK and MNPK treatments. N limitation further influenced soil microbial community structure and its dominated SOC decomposition. Specifically, Microbial communities transformed into a more oligotrophic-dominant condition (fungal, Acidobacteria, Chloroflexi) from copiotrophic-dominant (Proteobacteria, Actinobacteria) condition with increasing N limitation. Lysobacter genus and Blastocatellaceae family, in the bacterial communities along with the Mortierella elongata species in fungal communities, were markedly associated with the N limitation, which could be the critical biomarker that represented N limitation. Both correlation analysis and partial least squares path modeling showed significant positive effects of N limitation on the ratio of bacterial functional genes (Cellulase/Amylase), involved in recalcitrant SOC degradation.

Nonlinear correction of a laser scanning interference system based on a fiber ring resonator

The laser scanning interferometry system has been successfully applied to many measurement fields because of its efficient measurement ability. However, the practical application ability of this measurement method is restricted due to the laser tuning nonlinearity. In this paper, the fiber ring resonator is equidistant in the frequency domain, which is used as the external clock signal to resample the main interference signal so as to realize the equifrequency sampling of the laser scanning interference system and correct the tuning nonlinearity. The final experimental result shows that this method can effectively reduce the phase noise caused by tuning nonlinearity and improve the performance of the system.

Criticality analysis for safety-critical software in nuclear power plant distributed control system

Software criticality analysis examines the degree of contribution that each individual failure mode of a software component has on the reliability of software. Higher safety integrity levels are assigned to software modules whose failures cause an unacceptable impact on the operation of the system, and these levels require the implementation of more rigorous software quality assurance measures as defined in IEEE Std 1012 and in the customer’s system requirements specification. In this paper, a novel software criticality analysis method is proposed, the results of which can be used to guide the development of newly developed software and the procurement of Commercial-Off-The-Shelf (COTS) software. The software structure is first analyzed and the software is divided into modules according to their functions. Then the criticality levels of software components are preliminarily classified by means of a safety criticality preliminary analysis tree, followed by their verification through the software hazard and operability analysis (HAZOP). Finally, the target Safety Integrity Level (SIL) of each software module is determined based on its criticality level and the overall safety objective (i. e., SIL) of the system it resides in. As an example, this proposed method is applied to a nuclear power plant safety-critical system to demonstrate the detail application process and to verify the feasibility of the method. Compared with the existing software criticality analysis methods, this method has better operability and verifiability, and can be utilized as a technical guidance for the software criticality analysis of nuclear power plant digital control systems.