Effect of the combination of cognitive behavioral therapy and oral paroxetine hydrochloride in patients with post-stroke depression

Purpose: To determine the effects of combined use of cognitive behavioral therapy (CBT) and paroxetine hydrochloride tablets in patients with post-stroke depression (PSD), and its effect on scores on Hamilton Rating Scale for Depression (HAMD) and Stroke Specific Quality of Life Scale (SS-QOL). Methods: Clinical data for 96 patients with PSD who were treated in Dongying Traditional Chinese Hospital, Dongying City, China from June 2018 to June 2019 were retrospectively analyzed. Patients who met the inclusion criteria were divided into treatment group (TG, n = 48) and reference group (RG, n = 48) based on odd and even hospitalization numbers. Both groups received conventional treatment, but RG patients were in addition given clopidogrel, while TG received CBT in combination with paroxetine hydrochloride tablets. Clinical indices were evaluated in both groups before and after treatment. Moreover, therapeutic effects in the two different treatment methods on PSD, as well as on Hamilton Rating Scale for Depression (HAMD) and Stroke Specific Quality of Life Scale (SS-QOL) scores were analyzed. Results: After treatment, TG had lower HAMD score (p < 0.001), lower scores on modified Rankin scale, and few incidences of adverse reactions at 3, 7, 15 and 30 days of treatment (p < 0.05), but higher total clinical effectiveness and mean SS-QOL score (p < 0.05), when compared with RG. Conclusion: Combined use of CBT and oral paroxetine hydrochloride tablets may be a promising strategy for treating depression and enhancing the quality of life of PSD patients, as it greatly improves neurological deficit and prognosis. However, further clinical trials should be carried out prior to introducing it in clinical practice

Age-Related Decline in the Variation of Dynamic Functional Connectivity: A Resting State Analysis

Normal aging is typically characterized by abnormal resting-state functional connectivity (FC), including decreasing connectivity within networks and increasing connectivity between networks, under the assumption that the FC over the scan time was stationary. In fact, the resting-state FC has been shown in recent years to vary over time even within minutes, thus showing the great potential of intrinsic interactions and organization of the brain. In this article, we assumed that the dynamic FC consisted of an intrinsic dynamic balance in the resting brain and was altered with increasing age. Two groups of individuals (N = 36, ages 20–25 for the young group; N = 32, ages 60–85 for the senior group) were recruited from the public data of the Nathan Kline Institute. Phase randomization was first used to examine the reliability of the dynamic FC. Next, the variation in the dynamic FC and the energy ratio of the dynamic FC fluctuations within a higher frequency band were calculated and further checked for differences between groups by non-parametric permutation tests. The results robustly showed modularization of the dynamic FC variation, which declined with aging; moreover, the FC variation of the inter-network connections, which mainly consisted of the frontal-parietal network-associated and occipital-associated connections, decreased. In addition, a higher energy ratio in the higher FC fluctuation frequency band was observed in the senior group, which indicated the frequency interactions in the FC fluctuations. These results highly supported the basis of abnormality and compensation in the aging brain and might provide new insights into both aging and relevant compensatory mechanisms

An established protocol for generating transgenic wheat for wheat functional genomics via particle bombardment

Wheat is one of the most important food crops in the world and is considered one of the top targets in crop biotechnology. With the high-quality reference genomes of wheat and its relative species and the recent burst of genomic resources in Triticeae, demands to perform gene functional studies in wheat and genetic improvement have been rapidly increasing, requiring that production of transgenic wheat should become a routine technique. While established for more than 20 years, the particle bombardment-mediated wheat transformation has not become routine yet, with only a handful of labs being proficient in this technique. This could be due to, at least partly, the low transformation efficiency and the technical difficulties. Here, we describe the current version of this method through adaptation and optimization. We report the detailed protocol of producing transgenic wheat by the particle gun, including several critical steps, from the selection of appropriate explants (i.e., immature scutella), the preparation of DNA-coated gold particles, and several established strategies of tissue culture. More importantly, with over 20 years of experience in wheat transformation in our lab, we share the many technical details and recommendations and emphasize that the particle bombardment-mediated approach has fewer limitations in genotype dependency and vector construction when compared with the Agrobacterium-mediated methods. The particle bombardment-mediated method has been successful for over 30 wheat genotypes, from the tetraploid durum wheat to the hexaploid common wheat, from modern elite varieties to landraces. In conclusion, the particle bombardment-mediated wheat transformation has demonstrated its potential and wide applications, and the full set of protocol, experience, and successful reports in many wheat genotypes described here will further its impacts, making it a routine and robust technique in crop research labs worldwide

Factors associated with health literacy in rural areas of Central China: structural equation model

Abstract Background Health literacy is a strong predictor of health status. This study develops and tests a structural equation model to explore the factors that are associated with the health literacy level of rural residents in Central China. Methods The participants were recruited from a county-level city in Central China (N = 1164). Face-to-face interviews were conducted to complete the self-designed questionnaire of each participant. The questionnaire included items for the (1) demographic information, (2) socioeconomic status, and (3) health literacy of the participants. Mplus analyses were performed to evaluate the proposed model. Results The final model showed good fit for the data, and both demographic characteristics (i.e., age, BMI, and residence) and socioeconomic status (i.e., monthly income, occupation, and education level) were significantly associated with health literacy level. The effects of these two variables were − 0.277 (P < 0.05) and 0.615 (P < 0.001), respectively, and the model explained 70.2% of the variance in health literacy. Conclusions Health literacy was significantly associated with age, BMI, distance between residence and nearest medical institution, monthly income, occupation, and education level, whereas socioeconomic status was a dominant predictor of health literacy level. Targeting these factors might be helpful in allocating health resources rationally when performing health promotion work

Recognition of maize seed varieties based on hyperspectral imaging technology and integrated learning algorithms

Purity is an important factor of maize seed quality that affects yield, and traditional seed purity identification methods are costly or time-consuming. To achieve rapid and accurate detection of the purity of maize seeds, a method for identifying maize seed varieties, using random subspace integrated learning and hyperspectral imaging technology, was proposed. A hyperspectral image of the maize seed endosperm was collected to obtain a spectral image cube with a wavelength range of 400∼1,000 nm. Methods, including Standard Normal Variate (SNV), multiplicative Scatter Correction (MSC), and Savitzky–Golay First Derivative (SG1) were used to preprocess raw spectral data. Iteratively retains informative variables (IRIV) and competitive adaptive reweighted sampling (CARS) were used to reduce the dimensions of the spectral data. A recognition model of maize seed varieties was established using k-nearest neighbor (KNN), support vector machine (SVM), line discrimination analysis (LDA) and decision tree (DT). Among the preprocessing methods, MSC has the best effect. Among the dimensionality reduction methods, IRIV has the best performance. Among the base classifiers, LDA had the highest precision. To improve the precision in identifying maize seed varieties, LDA was used as the base classifier to establish a random subspace ensemble learning (RSEL) model. Using MSC-IRIV-RSEL, precision increased from 0.9333 to 0.9556, and the Kappa coefficient increased from 0.9174 to 0.9457. This study shows that the method based on hyperspectral imaging technology combined with subspace ensemble learning algorithm is a new method for maize seed purity recognition

Effects of size of zinc borate on the flame retardant properties of intumescent coatings

This paper is aimed at assessing the fire retardancy and thermal stability of intumescent flame retardant (IFR) containing ammonium polyphosphate (APP), pentaerythritol (PER), and melamine (MEL). Zinc borate (ZB) was added at the loading of 2%, 4%, 6%, 8%, 10%, and 12% by weight of IFR. The sizes of investigated ZB fall in 3 ranges: 1-2 μm, 2-5 μm, and 5-10 μm. The performance of APP/PER/MEL was investigated by using thermogravimetry analysis (TGA), cone calorimeter test, Fourier-transform infrared (FTIR) spectroscopy, scanning electron microscopy, and energy-dispersive spectrometry. The results obtained from the above experiments show that the incorporation of ZB can improve the fire protection performance. A 77% decrease in total smoke production and 84.6% decrease in total heat release were achieved for the addition of 2 wt% ZB (2-5 μm) in the IFR coating. TGA results indicate an increased amount of char residue. Compared to the control IFR coating, the char residue of IFR containing 2 wt% ZB (2-5 μm) has increased approximately 1.5-fold, 10-fold, and 25-fold, at 600°C, 700°C, and 800°C, respectively. The effective char formation results in excellent smoke suppression. Regarding smoke suppression performance, the order for smoke density is IFR/ZB (2-5 μm) < IFR/ZB (5-10 μm) < IFR/ZB (1-2 μm), regardless of investigated loading levels. The decline of smoke suppression performance for IFR/ZB (5-10 μm) and IFR/ZB (1-2 μm) is believed to be due to the poor char formation, as a result of a weak interaction of APP, PER, MEL, and ZB. This weak interaction is caused by the decrease in the specific surface area and agglomeration of ZB particles for IFR/ZB (5-10 μm) and IFR/ZB (1-2 μm), respectively