Steam explosion pretreatment enhances free/combined phytosterol extraction and utilization in rapeseed (Brassica napus L.) and its processed products: Insights from SPE-GC approach.

The study investigates the impact of steam explosion pretreatment on the distribution of free and combined phytosterols within rapeseed and its derived products. Utilizing solid phase extraction-gas chromatography (SPE-GC) analysis, we elucidated the composition and distribution of phytosterols in five rapeseed varieties and their corresponding processed oils and cakes. The results indicated that Zhongyou 516 and Xiwang 988 are richer in combined phytosterols, whereas Dadi 199, Zhongyouza 501, and Xiwang 291 have a greater concentration of free phytosterols. Steam explosion pretreatment significantly increased the extraction proportion of combined phytosterols in rapeseeds. Throughout the oil process, more than half of the total phytosterol content, specifically 57.0%, was transferred from the steam explosion-treated rapeseed into the rapeseed oil. The variety Xiwang 291 showed the highest efficiency in this transfer, achieving a rate of 61.7%. The study provides crucial data for the enhancement of rapeseed processing techniques and the efficient utilization of phytosterols. Moreover, the study highlights the potential use of the ratio of free to combined phytosterols as a discriminator for different rapeseed oil varieties, offering valuable insights for quality assurance and product differentiation in the industry.

Comprehensive profiling and evaluation of free/conjugated Phytosterols in crops using chemical derivatization coupled with UHPLC-ESI-QTOF-MS/MS.

Phytosterols are naturally existed in crops but their detection is constrained by sensitivity and accuracy due to the inefficient analytical approaches. This study hypothesizes that an untargeted analytical method combining chemical derivatization with ultrahigh performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry can identify the various composition and contents of phytosterols in different crops. The results showed that chemical derivatization significantly enhanced intensity of phytosterols compared with non-derivatized samples. Using precursor ion scanning (PIS) of m/z 252.0690, dansyl chloride-labeled phytosterols were identified, demonstrating that rapeseeds had the highest content of total phytosterol (3981.2 ± 95.3 mg/kg), followed by sunflower seeds, flaxseeds, corn and rice, respectively. Principal component analysis revealed significant variations in phytosterol distribution among 15 crop samples, suggesting the applicability of phytosterol profile as a marker for phytosterols-contained crops. Hence, the proposed analytic approach proves high efficiency and accuracy in determining phytosterols and advances the study for phytosterol-enriched crops.

Comprehensive physicochemical indicators analysis and quality evaluation model construction for the post-harvest ripening rapeseeds.

Rapeseed (Brassica napus L.) is the second largest globally cultivated oil crop, but the effects of post-harvested ripening on rapeseed quality is unclear and unpredictable. This study reveals the relationship between post-harvest ripening periods (PHR) and physicochemical quality of different rapeseed cultivars using comprehensive physicochemical indicators analysis. The results indicate that PHR led to a gradual decrease in chlorophyll, carotenoid and moisture content but continually increased oil and total phenol content (TPC). Besides, 295 lipid molecules from 13 lipid subclasses were identified, revealing that the relative content of triacylglycerol (TG) was progressively increased while diacylglycerol (DG) demonstrated a consistent decline throughout the PHR. Correlation analysis, hierarchical cluster analysis (HCA) and principal component analysis (PCA) were employed to construct and verify the comprehensive quality evaluation model for rapeseeds in PHR. This paper develops a comprehensive quality evaluation model for post-harvest ripening rapeseeds and advances the development of agricultural products.

The association between the number of food kinds and risk of depression in U.S. adults.

BACKGROUND: The association between the number of food kinds and the risk of depression in adults was examined. METHODS: According to the inclusion and exclusion criteria, a total of 4593 adults were included in the study. The number of food kinds was collected via 24‒hour dietary recalls. Depression was assessed using the Patient Health Questionnaire‒9. Logistic regression and restricted cubic spline models were applied to assess the association between the number of food kinds and the risk of depression. RESULTS: This study included 4593 study participants, 451 of whom were diagnosed with depression. The revised advantage ratios (with corresponding confidence intervals) for the prevalence of depression among individuals in the fourth quartiles of the number of food kinds (Q4) in comparison to the lowest quartile (Q1) were determined to be 0.59 (0.36‒0.96), respectively. According to our subgroup analyses, the number of food kinds was negatively associated with the risk of depression in females, participants aged 18‒45 and 45‒65 years, and participants with a body mass index (BMI) of 25 to 24.9 kg/m2. According to our dose‒response analysis, the number of food kinds was linearly associated with the risk of depression (Pfor nonlinear=0.5896). CONCLUSION: The risk of depression exhibited a linear and negative correlation with the number of food kinds. The results indicated that a diversified diet was an effective nonpharmacological approach that deserved further generalization.

Integrated MUSIC array for high-precision damage diagnosis in complex composite structures.

Guided Wave (GW)-based Multiple Signal Classification (MUSIC) damage imaging presents several advantages, such as high resolution, which makes it a promising technique for localizing damage in composite structures. However, the application of this technology in aircraft is confronted with various challenges. The variability in performance of MUSIC array sensors is attributed to material and manufacturing process dispersion. Additionally, the conventional wiring of MUSIC array sensors adds considerable weight and is not compatible with complex structural configurations. Furthermore, within intricate configurations, the attenuation of scattering signals induced by structural damage impacts the accuracy of imaging. Moreover, the manual and individual placement of sensors on structures, along with structural anisotropy, may introduce phase errors in the signals detected by MUSIC array sensors. This can lead to a reduction in the accuracy of MUSIC imaging and result in compromised long-term sensor reliability. This paper proposes a high-precision integrated MUSIC array for the diagnosis of complex composite damage. This approach aims to address the challenges related to damage imaging in materials with complex structures. Impedance curve screening and surface-mount co-curing technology are utilized to manage the performance variation of MUSIC array sensors, enhance layout uniformity, and improve long-term stability. Subsequently, a focus compensation algorithm is proposed within the integrated MUSIC design to enhance precision, reduce weight, and adapt to complex structures. The effectiveness of the proposed method is confirmed through experimental validation on an actual complex composite wing box segment, demonstrating a maximum error of 2 cm in locating impact damage.

Insights into the antibacterial activity and antibacterial mechanism of silver modified fullerene towards Staphylococcus aureus by multiple spectrometric examinations.

Clarifying the antibacterial mechanism of silver (Ag)-based materials is of great significance for the rational design, synthesis, and evaluation of antimicrobials. Herein, detailed description of the antibacterial mechanism of a synthesized silver deposited fullerene material (Ag(I)-C60) towards Staphylococcus aureus was surveyed from the point of view of DNA damage by ultraviolet-visible spectroscopy (UV-vis), inductively coupled plasma mass spectrometry (ICP-MS), and liquid chromatography-mass spectrometry (LC-MS). The model material, Ag(I)-C60, was prepared by liquid-liquid interfacial precipitation method, and characterized by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), thermos-gravimetric analysis (TGA), and nitrogen adsorption/desorption analysis. Ultra-efficient bacteriostatic rate of Ag(I)-C60 was found to be 88.98% under light irradiation for 20 min. UV-vis measurement of the composition changes of four DNA bases showed that they changed in the presence of Ag(I)-C60 under light irradiation, suggesting Ag(I)-C60 could destroy the cells and genetic material of Staphylococcus aureus and thereby inhibit its growth and reproduction. ICP-MS analysis demonstrated the releasing behavior of Ag+ from Ag-based materials. Finally, the transformation pathway of G, A, C, and T were measured by LC-MS, demonstrating the conversion of Adenine (m/z 136.06) to 8-OH-Ade (m/z 174.04). These collective results suggested that Ag(I)-C60 was a new ultra-efficient antibacterial by slowly releasing Ag+ in water and producing a large amount of ROS under light.

Multi-Dimensional Uniform Initialization Gaussian Mixture Model for Spar Crack Quantification under Uncertainty.

Guided Wave (GW)-based crack monitoring method as a promising method has been widely studied, as this method is sensitive to small cracks and can cover a wide monitoring range. Online crack quantification is difficult as the initiation and growth of crack are affected by various uncertainties. In addition, crack-sensitive GW features are influenced by time-varying conditions which further increase the difficulty in crack quantification. Considering these uncertainties, the Gaussian mixture model (GMM) is studied to model the probability distribution of GW features. To further improve the accuracy and stability of crack quantification under uncertainties, this paper proposes a multi-dimensional uniform initialization GMM. First, the multi-channel GW features are integrated to increase the accuracy of crack quantification, as GW features from different channels have different sensitivity to cracks. Then, the uniform initialization method is adopted to provide more stable initial parameters in the expectation-maximization algorithm. In addition, the relationship between the probability migration index of GMMs and crack length is calibrated with fatigue tests on prior specimens. Finally, the proposed method is applied for online crack quantification on the notched specimen of an aircraft spar with complex fan-shaped cracks under uncertainty.