Plasma Ionomic Profile and Interaction Patterns in Coronary Artery Disease Patients.

Humans are exposed to various chemical elements that have been associated with the development and progression of diseases such as coronary artery disease (CAD). Unlike previous research, we employed a multi-element approach to investigate CAD patients and those with comorbid conditions such as diabetes (CAD-DM2), high blood pressure (CAD-HBP), or high blood lipids (CAD-HBL). Plasma concentrations of 21 elements, including lithium (Li), boron (B), aluminum (Al), calcium (Ca), titanium (Ti), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), selenium (Se), strontium (Sr), cadmium (Cd), tin (Sn), stibium (Sb), barium (Ba), and lead (Pb), were measured in CAD patients (n = 201) and healthy subjects (n = 110) using inductively coupled plasma-mass spectrometry (ICP-MS). Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models were utilized to analyze the ionomic profiles. Spearman correlation analysis was employed to identify the interaction patterns among individual elements. We found that levels of Ba, Li, Ni, Zn and Pb were elevated in the CAD group compared to the healthy group, while Sb, Ca, Cu, Ti, Fe, and Se were lower. Furthermore, the CAD-DM2 group exhibited higher levels of Ni and Cd, while the CAD-HBP group showed lower levels of Co and Mn. In the CAD-HBL group, Ti was increased, whereas Ba, Cr, Cu, Co, Mn, and Ni were reduced. In conclusion, ionomic profiles can be utilized to differentiate CAD patients from healthy individuals, potentially providing insights for future treatment or dietary interventions.

Dual-learning Multi-hop Nonnegative Matrix Factorization for community detection.

As an important branch of network science, community detection has garnered significant attention. Among various community detection methods, nonnegative matrix factorization (NMF)-based community detection approaches have become a popular research topic. However, most NMF-based methods overlook the network's multi-hop information, let alone the community detection results specific to each hop of the network. In this paper, we propose Dual-learning Multi-hop NMF (DL-MHNMF), a method that considers not only the multi-hop connectivity between two nodes but also factors in the shared results across multiple hops and the impact of differences in the specific results at each hop on the shared outcomes. An efficient iterative optimization algorithm with guaranteed theoretical convergence is proposed for solving DL-MHNMF. Methodologically, by iteratively removing the specific results during the optimization process of DL-MHNMF, we achieve enhanced detection accuracy, which is also verified by subsequent experiments. Specifically, we compare fourteen algorithms on eleven publicly available datasets, and experimental results show that our algorithm outperforms most state-of-the-art methods. The source code is availiable at https://github.com/bx20000827/DL-MHNMF.git.

Impact of Mobile Apps in Conjunction With Percutaneous Endoscopic Gastrostomy on Patients' Complications, Quality of Life, and Health-Related Self-Care Behaviors: Randomized Clinical Trial.

BACKGROUND: Percutaneous endoscopic gastrostomy (PEG) is commonly chosen for long-term enteral nutrition support. However, common complications of PEG include wound infection, leakage, obstruction, bleeding, dislodgement, pneumonia, peritonitis, and more. The anticipation of these complications by both patients and their family caregivers underscores the essential requirement of ongoing technical guidance for the daily care of PEG and the adoption of preventative strategies. OBJECTIVE: This study aimed to establish and compare a health education program utilizing a tracking system for PEG using a mobile app (PEG app) and instant messaging software versus a paper-based health education program with instant messaging software. Their effectiveness in preventing complications, avoiding hospital readmissions, improving self-care practices, and enhancing quality of life outcomes was assessed. METHODS: A randomized controlled trial design was used, and the study sample consisted of patients from a medical center in central Taiwan who underwent thoracic surgery or gastroenterology procedures. Inclusion criteria were being a new case undergoing his or her first gastric tube insertion and having the ability to operate a smartphone. Exclusion criteria were cases requiring tube replacement or nasogastric tubes. A total of 74 participants were enrolled, with 37 participants in the experimental group and 37 participants in the control group. Data collection took place from hospitalization until 1 month after discharge. The experimental group received care using the gastric tube tracking system (PEG app) and the Line app that included phone, text, and photo capture capabilities, while the control group received routine nursing care and used the Line app. RESULTS: The experimental group demonstrated a significant reduction in the occurrence of complications compared with the control group (χ21=12.087, P=.001). Specifically, the occurrence of leakage events was significantly lower in the experimental group than in the control group (χ21=12.906, P=.001). However, the experimental group exhibited superior self-care ability compared with the control group (t72=2.203, P=.03). There was no significant difference in overall quality of life scores between the experimental and control groups (t72=1.603, P=.11). However, the experimental group showed better social aspects of quality of life than the control group (t72=2.164, P=.03). CONCLUSIONS: Integration of the PEG app with instant messaging can enhance self-care ability, improve social aspects of quality of life, and reduce complications. The study results suggest that the PEG app could be used as an adjunct tool to promote patients' self-directed management of their gastric tube at home, particularly for patients who have undergone their first PEG placement and are being discharged from the hospital. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2300071271; https://tinyurl.com/4vvy584e.

A semi-continuous efficient strategy for removing phosphorus and nitrogen from eel aquaculture wastewater using the self-flocculating microalga Desmodesmus sp. PW1.

The phosphorus content in eel aquaculture wastewater exceeds the discharge standard, and the amount of wastewater discharged is substantial. Therefore, there is an urgent need to explore an economical and efficient method of treating aquaculture wastewater. This study explored the use of Desmodesmus sp. PW1, a type of microalgae, to treat eel aquaculture wastewater. By optimizing the conditions, Desmodesmus sp. PW1 achieved a total phosphorus (TP) removal efficiency of 92.3%, as well as total nitrogen (TN) and ammonia nitrogen (NH4+-N) removal efficiency of 99%, using a photoperiod of 24:0, a temperature of 25 °C, and an inoculation amount of 15%. Furthermore, Desmodesmus sp. PW1 demonstrated a high self-flocculating efficiency (>90%) within 100 min of settling, which facilitated biomass recovery. Subsequently, a semi-continuous treatment process mode was established with a sewage renewal rate of 90%. The results showed that after four rounds of sewage renewal operations, the microalgae biomass in the sewage treatment system could be maintained between 160.0 and 220.0 mg/L, and the average removal rate of TP was 0.13 mg/(L * h). The lipid content of algae cells collected in the semi-continuous treatment system for eel aquaculture wastewater was as high as 36.5%, and the biodiesel properties met the biodiesel standards authorized by Europe and the United States. Overall, this study provides an economical and effective strategy for converting wastewater into high-value microalgae products.

Preparation, multi-scale structures, and functionalities of acetylated starch: An updated review.

Acetylated starch has been widely used as food additives. However, there was limited information available regarding the impact of acetylation on starch structure and functionalities, as well as the advanced acetylation technologies. This review aimed to summarize current methods for starch acetylation and discuss the structure and functionalities of acetylated starch. Innovative techniques, such as milling, microwave, pulsed electric fields, ultrasonic, and extrusion, could be employed for environmental-friendly synthesis of acetylated starch. Acetylation led to the degradation of starch structures and weakening of the interactions between starch molecules, resulting in the disorganization of starch multi-scale ordered structure. The introduction of acetyl groups retarded the self-reassembly behavior of starch, leading to increased solubility, clarity, and softness of starch-based hydrogels. Moreover, the acetyl groups improved water/oil absorption capacity, emulsifiability, film-forming properties, and colonic fermentability of starch, while reduced the susceptibility of starch molecules to enzymes. Importantly, starch functionalities were largely influenced by the decoration of acetyl groups on starch molecules, while the impact of multi-scale ordered structures on starch physicochemical properties was relatively minor. These findings will aid in the design of structured acetylated starch with desirable functionalities.

DCTPP1, a reliable Q-biomarker for comprehensive evaluation of the quality of tripterygium glycoside tablets based on chemical references.

BACKGROUND: As first-line clinical drugs, tripterygium glycoside tablets (TGTs) often have inconsistent efficacy and toxic side effects, mainly due to inadequate quality control. Therefore, clinically relevant quality standards for TGTs are urgently required. PURPOSE: Based on chemical substances and considering pharmacological efficacy, we aimed to develop an effective quality evaluation method for TGTs. METHODS: Representative commercial samples of TGTs were collected from different manufacturers, and qualitative UHPLC/LTQ-Orbitrap-MS and quantitative UHPLC-MS/MS analysis methods were successfully applied to evaluate their quality similarities and differences based on their chemical properties. Then the anti-immunity, anti-inflammatory and antitumor activities of TGTs and related monomers were evaluated using Jurkat, RAW264.7, MIA PaCa-2, and PANC-1 as cellular models. Subsequently, we predicted and verified small molecule-DCTPP1 interactions via molecular docking using the established DCTPP1 enzymatic activity assay. Finally, we performed a gray relational analysis to evaluate the chemical characteristics and biological effects of TGTs produced by different manufacturers. RESULTS: We collected 24 batches of TGTs (D01-D24) from 5 manufacturers (Co. A, Co. B, Co. C, Co. D, Co. E) for quality evaluation. The chemical composition analysis revealed significant differences in the substance bases of the samples. The D02, D18-D20 samples from Co. B constituted a separate group that differed from other samples, mainly in their absence of diterpenoids and triterpenoids, including triptolide, triptophenolide, and triptonide. In vitro anti-immunity, antitumor and anti-inflammatory tests using the same TGT concentration revealed that, except for D02, D18-D20, the remaining 20 samples exhibited different degrees of anti-immunity, antitumor and anti-inflammatory activity. Our experiments verified that triptolide, triptophenolide, and triptonide were all DCTPP1 inhibitors, and that TGTs generally exhibited DCTPP1 enzyme inhibitory activity. Moreover, the inhibitory activity of D02, D18-D20 samples from Co. B was much lower than that of the other samples, with a nearly tenfold difference in IC50. Further comprehensive analysis revealed a high correlation between DCTPP1 enzyme inhibition activity and the anti-immunity and antitumor and anti-inflammatory activities of these samples. CONCLUSION: The established DCTPP1 enzymatic activity assay proved suitable for quantitative pharmacological and pharmaceutical analysis to complement the existing quality control system for TGTs and to evaluate their effectiveness.

Lycopene in hydrophobic deep eutectic solvent with natural catalysts: A promising strategy to simultaneously promote lycopene Z-isomerization and extraction.

Lycopene Z-isomerization and degradation in a series of hydrophobic natural deep eutectic solvents (HNDES) was firstly studied. The highest lycopene retention (about 84.6%) was found in HNDES composed of thymol and menthol (TM), and fatty acid-based HNDES promoted lycopene Z-isomerization (about 70% for total Z-isomers) and degradation. The addition of allyl isothiocyanate (AITC), diallyl disulfide (DADS) and capric acid into TM promoted Z-isomerization of lycopene (80% for total Z-isomers), especially 5Z-isomer (>30%), while lycopene remaining rate in TM/-capric acid was below 20%. During lycopene extraction from tomato power and watermelon juice by TM, the ratios of Z-isomer significantly (p < 0.05) increased especially with AITC and DADS (up to about 80%), and extraction yields increased even > 100% with capric acid. Lycopene in TM/-capric acid extracts showed low degradation with Z-isomers increasing during storage. TM with capric acid could simultaneously promote lycopene Z-isomerization and extraction.

Whole genome sequencing and analysis of Armillaria gallica Jzi34 symbiotic with Gastrodia elata.

BACKGROUND: Armillaria species are plant pathogens, but a few Armillaria species can establish a symbiotic relationship with Gastrodia elata, a rootless and leafless orchid, that is used as a Chinese herbal medicine. Armillaria is a nutrient source for the growth of G. elata. However, there are few reports on the molecular mechanism of symbiosis between Armillaria species and G. elata. The genome sequencing and analysis of Armillaria symbiotic with G. elata would provide genomic information for further studying the molecular mechanism of symbiosis. RESULTS: The de novo genome assembly was performed with the PacBio Sequel platform and Illumina NovaSeq PE150 for the A. gallica Jzi34 strain, which was symbiotic with G. elata. Its genome assembly contained ~ 79.9 Mbp and consisted of 60 contigs with an N50 of 2,535,910 bp. There were only 4.1% repetitive sequences in the genome assembly. Functional annotation analysis revealed a total of 16,280 protein coding genes. Compared with the other five genomes of Armillaria, the carbohydrate enzyme gene family of the genome was significantly contracted, while it had the largest set of glycosyl transferase (GT) genes. It also had an expansion of auxiliary activity enzymes AA3-2 gene subfamily and cytochrome P450 genes. The synteny analysis result of P450 genes reveals that the evolutionary relationship of P450 proteins between A. gallica Jzi34 and other four Armillaria was complex. CONCLUSIONS: These characteristics may be beneficial for establishing a symbiotic relationship with G. elata. These results explore the characteristics of A. gallica Jzi34 from a genomic perspective and provide an important genomic resource for further detailed study of Armillaria. This will help to further study the symbiotic mechanism between A. gallica and G. elata.

Community Detection via Multihop Nonnegative Matrix Factorization.

Community detection aims at finding all densely connected communities in a network, which serves as a fundamental graph tool for many applications, such as identification of protein functional modules, image segmentation, social circle discovery, to name a few. Recently, nonnegative matrix factorization (NMF)-based community detection methods have attracted significant attention. However, most existing methods neglect the multihop connectivity patterns in a network, which turn out to be practically useful for community detection. In this article, we first propose a novel community detection method, namely multihop NMF (MHNMF for brevity), which takes into account the multihop connectivity patterns in a network. Subsequently, we derive an efficient algorithm to optimize MHNMF and theoretically analyze its computational complexity and convergence. Experimental results on 12 real-world benchmark networks demonstrate that MHNMF outperforms 12 state-of-the-art community detection methods.

Deglycosylation Inactivation Initiated by a Novel Periplasmic Dehydrogenase Complex Provides a Novel Strategy for Eliminating the Recalcitrant Antibiotic Kanamycin.

Biodegradation using enzyme-based systems is a promising approach to minimize antibiotic loads in the environment. Aminoglycosides are refractory antibiotics that are generally considered non-biodegradable. Here, we provide evidence that kanamycin, a common aminoglycoside antibiotic, can be degraded by an environmental bacterium through deglycosylation of its 4'-amino sugar. The unprecedented deglycosylation inactivation of kanamycin is initiated by a novel periplasmic dehydrogenase complex, which we designated AquKGD, composed of a flavin adenine dinucleotide-dependent dehydrogenase (AquKGDα) and a small subunit (AquKGDγ) containing a twin-arginine signal sequence. We demonstrate that the formation of the AquKGDα-AquKGDγ complex is required for both the degradation activity of AquKGD and its translocation into the periplasm. Native AquKGD was successfully expressed in the periplasmic space of Escherichia coli, and physicochemical analysis indicated that AquKGD is a stable enzyme. AquKGD showed excellent degradation performance, and complete elimination of kanamycin from actual kanamycin manufacturing waste was achieved with immobilized AquKGD. Ecotoxicity and cytotoxicity tests suggest that AquKGD-mediated degradation produces less harmful degradation products. Thus, we propose a novel enzymatic antibiotic inactivation strategy for effective and safe treatment of recalcitrant kanamycin residues.

Fabrication of high strength cold-set sodium alginate/whey protein nanofiber double network hydrogels and their interaction with curcumin.

Enhancing the bio-based hydrogels strength is fundamental to extend their engineering applications. In this study, high strength cold-set sodium alginate/whey protein nanofiber (SA/WPN) double network hydrogels were prepared and their interaction with curcumin (Cur) was studied. Our results indicated that the rheological and textural properties of SA/WPN double network hydrogels were enhanced with increasing WPN by forming SA-COO--Ca2+--OOC-WPN bridge through electrostatic interactions. The storage modulus (768.2 Pa), hardness (273.3 g), adhesiveness (318.7 g·sec) and cohesiveness (0.464) of SA/WPN50 (WPN concentration of 50 mg/mL) double network hydrogels were 3.75, 2.26, 3.76 and 2.19 times higher than those of SA hydrogels, respectively. Cur was combined with SA/WPN hydrogels through hydrogen bonding, van der Waals forces and hydrophobic interactions with an encapsulation efficiency of 91.6 ± 0.8 %, and the crystalline state was changed after binding. In conclusion, SA/WPN double network hydrogels can be enhanced by the addition of WPN and have potential as carriers for hydrophobic bioactive substances.

Real-time response counterattack strategy of tolerant microalgae Chlorella vulgaris MBFJNU-1 in original swine wastewater and free ammonia.

This work was the first time to systematically clarify the potential tolerance mechanism of an indigenous Chlorella vulgaris MBFJNU-1 towards the free ammonia (FA) during the original swine wastewater (OSW) treatment by transcriptome analysis using C. vulgaris UETX395 as the control group. The obtained results showed that C. vulgaris MBFJNU-1 was found to be more resistant to the high levels of FA (115 mg/L) and OSW in comparison to C. vulgaris UETX395 (38 mg/L). Moreover, the transcriptomic results stated that some key pathways from arginine biosynthesis, electron generation and transmission, ATP synthesis in chloroplasts, and glutathione synthesis of C. vulgaris MBFJNU-1 were greatly related with the OSW and FA. Additionally, C. vulgaris MBFJNU-1 in OSW and FA performed similar results in the common differentially expressed genes from these mentioned pathways. Overall, these obtained results deliver essential details in microalgal biotechnology to treat swine wastewater and high free ammonia wastewater.

Extraction and identification of steroidal saponins from Polygonatum cyrtonema Hua using natural deep eutectic solvent-synergistic quartz sand-assisted extraction method.

In this study, quartz sand with particularly sharp nanoscale edges acted like a nanoscale knife physically cut cells of Polygonatum cyrtonema Hua into nanosized particles and was synergized with natural deep eutectic solvent to extract steroidal saponins of Polygonatum cyrtonema Hua. The natural deep eutectic solvent (choline chloride-lactic acid)-synergistic quartz sand-assisted extraction was optimized using response surface methodology. The steroidal saponins purified with AB-8 macroporous resin were identified using ultra-high-performance liquid chromatography-triple time of flight mass spectrometry. The results showed that the experimental total saponins content value (36.97 ± 0.12 mg dioscin equivalent/g dry weight) at optimal extraction conditions with a temperature of 68°C, a rotational speed of 20 400 rpm, shear time of 4.3 min, the liquid-solid ratio of 38 ml/g, was close to the maximum possible theoretical value (36.64 mg dioscin equivalent/g dry weight). A total of 20 steroidal saponins were identified, among which the content of (25R)-Kingianoside E was the highest (102.66 ± 3.47 mg/g). Furthermore, a new steroid saponin (3ß,25S)-26-(ß-D-glucopyranosyloxy)-22-hydroxyfurost-5-en-3-yl 4-O-ß-D-glucopyranosyl-ß-D-galactopyranoside+Glc was found for the first time. These results revealed that natural deep eutectic solvent-synergistic quartz sand-assisted extraction was an efficient and green method to extract a variety of steroidal saponins.

miR-6076 rs1463411 polymorphisms are associated with bleeding during clopidogrel treatment in patients with acute coronary syndrome.

Bleeding is a major adverse event during clopidogrel treatment in patients with acute coronary syndrome (ACS). However, the potential mechanism affecting bleeding among individuals is unclear. Herein, we investigated the involvement of CYP2C19*2 and CYP2C19*3, as well as 10 miRNA polymorphisms, in bleeding in Chinese patients with ACS during the first year of clopidogrel treatment. The miR-6076 rs1463411 G polymorphism was significantly associated with the risk of bleeding (P < 0.001), and the rs1463411 GT + GG genotype significantly increased the risk of bleeding (adjusted odds ratio, 6.09; 95% confidence interval, 1.09-34.0; P < 0.001). Dual luciferase assay showed that miR-6076 significantly decreased the mRNA expression of P2RY12 (P < 0.05). P2RY12 mRNA and protein levels were significantly lower in cells transfected with miR-6076-G than in cells transfected with miR-6076-T (P < 0.05). The findings indicate that miR-6076 targets P2RY12 mRNA and that miR-6076 rs1463411 T/G polymorphisms differentially regulate P2RY12 mRNA and protein levels in cells. rs1463411 G polymorphism may increase the risk of bleeding during clopidogrel treatment in patients with ACS.

Pilot-scale remediation of rare earth elements ammonium wastewater by Chlamydomonas sp. YC in summer under outdoor conditions.

This work evaluated the performance of real rare earth elements (REEs) wastewater purification and carbon dioxide (CO2) fixation by Chlamydomonas sp. YC with pilot-scale airlift-photobioreactors (AL-PBRs), tubular photobioreactors (TB-PBRs) and raceway ponds (ORWPs) under high-temperature outdoor conditions in summer. The obtained results showed that Chlamydomonas sp. YC at 1 g/L oyster shell piece (OSP) and 3 % CO2 had the highest biomass (1.9 g/L) and NH4+-N removal efficiency (34.0 %) during the REEs wastewater treatment. Among the selected photobioreactors, Chlamydomonas sp. YC to treat real REEs wastewater at 3 % CO2 under high-temperature outdoor conditions attained the highest biomass (2.3 g/L) in the TB-PBRs with the best NH4+-N removal efficiency (43.0 %). Furthermore, the input cost and CO2 net sequestration evaluation revealed that TB-PBRs was more economical photobioreactors to treat REEs wastewater and fix CO2 by Chlamydomonas sp. YC, providing some vital scientific details for REEs wastewater and CO2 fixation by microalgal biotechnology.

Unsupervised Feature Selection via Graph Regularized Nonnegative CP Decomposition.

Unsupervised feature selection has attracted remarkable attention recently. With the development of data acquisition technology, multi-dimensional tensor data has been appeared in enormous real-world applications. However, most existing unsupervised feature selection methods are non-tensor-based which results the vectorization of tensor data as a preprocessing step. This seemingly ordinary operation has led to an unnecessary loss of the multi-dimensional structural information and eventually restricted the quality of the selected features. To overcome the limitation, in this paper, we propose a novel unsupervised feature selection model: Nonnegative tensor CP (CANDECOMP/PARAFAC) decomposition based unsupervised feature selection, CPUFS for short. In specific, we devise new tensor-oriented linear classifier and feature selection matrix for CPUFS. In addition, CPUFS simultaneously conducts graph regularized nonnegative CP decomposition and newly-designed tensor-oriented pseudo label regression and feature selection to fully preserve the multi-dimensional data structure. To solve the CPUFS model, we propose an efficient iterative optimization algorithm with theoretically guaranteed convergence, whose computational complexity scales linearly in the number of features. A variation of the CPUFS model by incorporating nonnegativity into the linear classifier, namely CPUFSnn, is also proposed and studied. Experimental results on ten real-world benchmark datasets demonstrate the effectiveness of both CPUFS and CPUFSnn over the state-of-the-arts.

Determination of Characteristic Volatile Component Fingerprint of Peucedanum Praeruptorum Dunn at Different Harvest Periods Based on HS-GC-IMS.

BACKGROUND: Peucedanum praeruptorum Dunn (PPD) is a Chinese herbal medicine with medicinal value. Clinical studies have shown that PPD has protective effects against wind-heat, cough, asthma, cardiovascular diseases, and cancer. Therefore, cultivation of PPD is becoming more common. However, it has been difficult to determine the optimal harvest period for botanical Chinese medicines such as PPD. OBJECTIVES: Odor characteristics are directly related to the chemical components contained in traditional Chinese medicines. In particular, for traditional Chinese medicines such as PPD that are rich in volatile components, higher quality usually means more beneficial volatile components. The purpose of this study was to analyze changes in PPD volatile components across different harvest periods, and provide the basis for the identification of the ideal harvest period to ensure PPD quality. METHODS: We measured the volatile components of PPD at different harvest periods using HS-GC-IMS to characterize its volatile component fingerprint at different harvest periods. RESULTS: We identified 80 volatile components in PPD across five harvest periods, and combined complex heatmap and PCA methods distinguish the characteristics of the different harvest periods, and used ion mobility spectrometry to determine the volatile organic compounds (VOCs), which mainly included compounds such as olefins, esters, alcohols, aldehydes, and ketones, and determined that the abundance of volatile components reached a peak in December. CONCLUSIONS: The fingerprint determination of characteristic volatile components based on HS-GC-IMS can distinguish PPD in different harvest periods. HIGHLIGHTS: We used HS-GC-IMS to determine the characteristic fingerprint of volatile components from PPD across different harvest periods. This approach differs from past studies, which have determined the optimal harvest time of medicinal materials based on only the content of a single active ingredient.

Deep eutectic solvent on extraction of flavonoid glycosides from Dendrobium officinale and rapid identification with UPLC-triple-TOF/MS.

In this study, ultrasonic-assisted deep eutectic solvent (DES) method was used to extract flavonoids from Dendrobium officinale. The mechanism of DESs extraction differences was investigated by physicochemical characterization and molecular dynamics simulation experiments. Moreover, flavonoids from Dendrobium officinale were rapidly identified and quantitatively analyzed by UPLC-Triple-TOF/MS without removing DES. The results showed choline chloride-lactic acid (Chol-Lac) had the best extraction effect among forty groups of DESs, the extraction yield was up to 35.23 ± 2.12 mg/g. It was speculated that the tight hydrogen bond structure was the key to the better extraction ability of Chol-Lac. Meanwhile, the viscosity was the main physical parameter reflecting the hydrogen bond structure of DES. Fourteen flavonoid glycosides were identified, among which the content of rutin (1.94 ± 0.24 mg/g) was the highest. And the results of cluster analysis showed that different DESs had great differences in the extraction of flavonoid glycosides.

A novel very small granular starch from Chlorella sp. MBFJNU-17.

Novel resources of very small granular starch are of great interests to food scientists. We previously found Chlorella sp. MBFJNU-17 contained small granular starch but whether the MBFJNU-17 was a novel resource of very small granular starch remained unresolved. This study isolated and characterized the starch from MBFJNU-17 in comparison with quinoa starch (a typical very small granular starch), and discussed whether the MBFJNU-17 could be a resource of very small granular starch. Results showed that chlorella starch displayed a smaller size (1024 nm) than quinoa starch did (1107 nm), suggesting MBFJNU-17 was a good resource of very small granular starch. Additionally, chlorella starch had less amylose, higher proportion of long amylopectin branches, more ordered structures, thinner amorphous lamellae, better paste thermostability, and slower enzymatic digestion than quinoa starch did. These findings indicated that Chlorella sp. MBFJNU-17 was a novel resource of very small granular starch with desirable thermostability and nutritional attributes.

Stable isotope and elemental profiles determine geographical origin of saffron from China and Iran.

Origin verification of high-value saffron is essential for fair trade and to protect consumers' interests and rights. A traceability method using elemental content (% C and % N) and stable isotopes (δ13C, δ2H, δ18O, and δ15N) combined with chemometrics was developed to discriminate saffron from Iran and China and classify major domestic production areas in China. Results showed that Iranian samples had lower % C and % N contents but higher δ13C values than Chinese origin saffron, with δ13C acting as an important variable for origin discrimination. Moreover, δ2H and δ13C isotopes were found to be important variables to classify Chinese regional saffron origin. Two supervised pattern recognition models (PLS-DA) developed to classify Iranian and Chinese saffron, and regional Chinese saffron had a discrimination accuracy of 85.0 % and 80.2 %, respectively. These models provide the basis for a new regulatory inspection procedure to verify saffron origin and label claims, minimizing fraudulent mislabeling and adding value to saffron from specific regions.