Targeting circ-0034880-enriched tumor extracellular vesicles to impede SPP1highCD206+ pro-tumor macrophages mediated pre-metastatic niche formation in colorectal cancer liver metastasis.

BACKGROUND: Information transmission between primary tumor cells and immunocytes or stromal cells in distal organs is a critical factor in the formation of pre-metastatic niche (PMN). Understanding this mechanism is essential for developing effective therapeutic strategy against tumor metastasis. Our study aims to prove the hypothesis that circ-0034880-enriched tumor-derived extracellular vesicles (TEVs) mediate the formation of PMN and colorectal cancer liver metastasis (CRLM), and targeting circ-0034880-enriched TEVs might be an effective therapeutic strategy against PMN formation and CRLM. METHODS: We utilized qPCR and FISH to measure circRNAs expression levels in human CRC plasma, primary CRC tissues, and liver metastatic tissues. Additionally, we employed immunofluorescence, RNA sequencing, and in vivo experiments to assess the effect mechanism of circ-0034880-enriched TEVs on PMN formation and CRC metastasis. DARTS, CETSA and computational docking modeling were applied to explore the pharmacological effects of Ginsenoside Rb1 in impeding PMN formation. RESULTS: We found that circ-0034880 was highly enriched in plasma extracellular vesicles (EVs) derived from CRC patients and closely associated with CRLM. Functionally, circ-0034880-enriched TEVs entered the liver tissues and were absorbed by macrophages in the liver through bloodstream. Mechanically, TEVs-released circ-0034880 enhanced the activation of SPP1highCD206+ pro-tumor macrophages, reshaping the metastasis-supportive host stromal microenvironment and promoting overt metastasis. Importantly, our mechanistic findings led us to discover that the natural product Ginsenoside Rb1 impeded the activation of SPP1highCD206+ pro-tumor macrophages by reducing circ-0034880 biogenesis, thereby suppressing PMN formation and inhibiting CRLM. CONCLUSIONS: Circ-0034880-enriched TEVs facilitate strong interaction between primary tumor cells and SPP1highCD206+ pro-tumor macrophages, promoting PMN formation and CRLM. These findings suggest the potential of using Ginsenoside Rb1 as an alternative therapeutic agent to reshape PMN formation and prevent CRLM.

Neutrophil extracellular traps mediated by platelet microvesicles promote thrombosis and brain injury in acute ischemic stroke.

AIMS: Neutrophil extracellular traps (NETs) have been implicated in thrombotic diseases. There is no definitive explanation for how NETs form during acute ischemic strokes (AIS). The purpose of our study was to investigate the potential mechanism and role of NETs formation in the AIS process. METHODS: As well as 45 healthy subjects, 45 patients with AIS had ELISA tests performed to detect NET markers. Expression of high-mobility group box 1 (HMGB1) on platelet microvesicles (PMVs) was analyzed by flow cytometry in healthy subjects and AIS patients' blood samples. We established middle cerebral artery occlusion (MCAO) mice model to elucidate the interaction between PMPs and NETs. RESULTS: A significant elevation in NET markers was found in patient plasma in AIS patients, and neutrophils generated more NETs from patients' neutrophils. HMGB1 expression was upregulated on PMVs from AIS patients and induced NET formation. NETs enhanced Procoagulant activity (PCA) through tissue factor and via platelet activation. Targeting lactadherin in genetical and in pharmacology could regulate the formation of NETs in MCAO model. CONCLUSIONS: NETs mediated by PMVs derived HMGB1 exacerbate thrombosis and brain injury in AIS. Video Abstract.

Integration of Single-Cell and Bulk RNA-seq Data to Identify the Cancer-Associated Fibroblast Subtypes and Risk Model in Glioma.

Cancer-associated fibroblasts (CAFs) are an important component of the stroma. Studies showed that CAFs were pivotally in glioma progression which have long been considered a promising therapeutic target. Therefore, the identification of prognostic CAF markers might facilitate the development of novel diagnostic and therapeutic approaches. A total of 1333 glioma samples were obtained from the TCGA and CGGA datasets. The EPIC, MCP-counter, and xCell algorithms were used to evaluate the relative proportion of CAFs in glioma. CAF markers were identified by the single-cell RNA-seq datasets (GSE141383) from the Tumor Immune Single-Cell Hub database. Unsupervised consensus clustering was used to divide the glioma patients into different distinct subgroups. The least absolute shrinkage and selection operator regression model was utilized to establish a CAF-related signature (CRS). Finally, the prognostic CAF markers were further validated in clinical specimens by RT‒qPCR. Combined single-cell RNA-seq analysis and differential expression analysis of samples with high and low proportions of CAFs revealed 23 prognostic CAF markers. By using unsupervised consensus clustering, glioma patients were divided into two distinct subtypes. Subsequently, based on 18 differentially expressed prognostic CAF markers between the two CAF subtypes, we developed and validated a new CRS model (including PCOLCE, TIMP1, and CLIC1). The nomogram and calibration curves indicated that the CRS was an accurate prognostic marker for glioma. In addition, patients in the high-CRS score group had higher immune infiltration and tumor mutation burden levels. Moreover, the CRS score had the potential to predict the response to immune checkpoint blockade (ICB) therapy and chemotherapy. Finally, the expression profiles of three CAF markers were verified by RT‒qPCR. In general, our study classified glioma patients into distinct subgroups based on CAF markers, which will facilitate the development of individualized therapy. We also provided insights into the role of the CRS in predicting the response to ICB and chemotherapy in glioma patients.

Screening of Protein-Based Ultrasmall Nanozymes for Building Cell-Mimicking Catalytic Vesicles.

Enzymes are an important component for bottom-up building of synthetic/artificial cells. Nanozymes are nanomaterials with intrinsic enzyme-like properties, however, the construction of synthetic cells using nanozymes is difficult owing to their high surface energy or large size. Herein, the authors show a protein-based general platform that biomimetically integrates various ultrasmall metal nanozymes into protein shells. Specifically, eight metal-based ultrasmall nano-particles/clusters are in situ incorporated into ferritin nanocages that are self-assembled by 24 subunits of ferritin heavy chain. As a nanozyme generator, such a platform is suitable for screening the desired enzyme-like activities, including peroxidase (POD), oxidase (OXD), catalase (CAT) and superoxide dismutase (SOD). After screening, it is found that Ru intrinsically possesses the highest POD-like and CAT-like activities, while Mn and Pt show the highest OXD-like and SOD-like activities, respectively. Additionally, the inducers/inhibitors of various nanozymes are screened from more than 50 compounds to improve or inhibit their enzyme-like activities. Based on the screened nanozymes and their inhibitors, a proof-of-conceptually constructs cell-mimicking catalytic vesicles to mimic or modulate the events of redox homeostasis in living cells. This study offers a type of artificial metalloenzyme based on nanotechnology and shows a choice for bottom-up enzyme-based synthetic cell systems in a fully synthetic manner.

Formation of Iridium(III) and Rhodium(III) Amine, Imine, and Amido Complexes Based on Pyridine-Amine Ligands: Structural Diversity Arising from Reaction Conditions, Substituent Variation, and Metal Centers.

Herein, we present the different coordination modes of half-sandwich iridium(III) and rhodium(III) complexes based on pyridine-amine ligands. The pyridyl-amine iridium(III) and rhodium(III) complexes, the corresponding oxidation pyridyl-imine products, and 16-electron pyridyl-amido complexes can be obtained through the change in reaction conditions (nitrogen/adventitious oxygen atmosphere, reaction time, and solvents) and structural variations in the metal and ligand. Overall, the reaction of pyridine-amine ligands with [(η5-C5(CH3)5)MCl2]2 (M = Ir or Rh) in the presence of adventitious oxygen afforded the oxidized pyridyl-imine complexes. The possible mechanism for the oxidation of iridium(III) and rhodium(III) amine complexes was confirmed by the detection of the byproduct hydrogen peroxide. Moreover, the formation of pyridyl-amine complexes was favored when nonpolar solvent CH2Cl2 was used instead of CH3OH. The rarely reported complex with [(η5-Cp*)IrCl3] anions can also be obtained without the addition of NH4PF6. The introduction of the sterically bulky i-Bu group on the bridge carbon of the ligand led to the formation of stable 16-electron pyridyl-amido complexes. The pyridyl-amine iridium(III) and rhodium(III) complexes were also synthesized under a N2 atmosphere, and no H2O2 was detected in the whole process. In particular, the aqueous solution stability and in vitro cytotoxicity toward A549 and HeLa human cancer cells of these complexes were also evaluated. No obvious selectivity was observed for cancer cells versus normal cells with these complexes. Notably, the represented complex 5a can promote an increase in the reactive oxygen species level and induce cell death via apoptosis.

Increasing Anticancer Activity with Phosphine Ligation in Zwitterionic Half-Sandwich Iridium(III), Rhodium(III), and Ruthenium(II) Complexes.

The synthesis and biological assessment of neutral or cationic platinum group metal-based anticancer complexes have been extremely studied, whereas there are few reports on the corresponding zwitterionic complexes. Herein, the synthesis, characterization, and bioactivity of zwitterionic half-sandwich phosphine-imine iridium(III), rhodium(III), and ruthenium(II) complexes were presented. The sulfonated phosphine-imine ligand and a group of zwitterionic half-sandwich P,N-chelating organometallic complexes were fully characterized by nuclear magnetic resonance (NMR), mass spectrum (electrospray ionization, ESI), elemental analysis, and X-ray crystallography. The solution stability of these complexes and their spectral properties were also determined. Notably, almost all of these complexes showed enhanced anticancer activity against model HeLa and A549 cancer cells than the corresponding zwitterionic pyridyl-imine N,N-chelating iridium(III) and ruthenium(II) complexes, which have exhibited inactive or low active in our previous work. The increase in the lipophilic property and intracellular uptake levels of these zwitterionic P,N-chelating complexes appeared to be associated with their superior cytotoxicity. In addition, these complexes showed biomolecular interactions with bovine serum albumin (BSA). The flow cytometry studies indicated that the representative complex Ir1 could induce early-stage apoptosis in A549 cells. Further, confocal microscopy imaging analysis displayed that Ir1 entered A549 cells through the energy-dependent pathway, targeted lysosome, and could cause lysosomal damage. In particular, these complexes could impede cell migration in A549 cells.

Development of CRISPR-Cas9 genome editing system in Talaromyces marneffei.

Talaromyces marneffei is an important pathogenic thermally dimorphic fungus causing systemic talaromycosis mainly prevalent in Southeast Asia. The dimorphic transition between mycelium and yeast is considered crucial for the pathogenicity of T. marneffei. However, the lack of genetic toolbox has been a major impediment for understanding its pathogenicity. Here a CRISPR-Cas9 system was developed to facilitate genetic manipulations in this organism. In this study, the CRISPR-Cas9 gene editing system uses a native U6 snRNA promoter from T. marneffei to drive the expression of sgRNA. Employing this system and PEG-mediated protoplast transformation, the sakA gene was mutated. Sanger sequencing confirmed nearly 40% site-directed mutation rate. The phenotype analysis confirmed the sakA gene function in T. marneffei dimorphic transition. Our study provided a powerful genome-manipulating tool, which could accelerate studies on T. marneffei for further revealing the mechanisms of its pathogenicity.

Synthesis and biological evaluation of zwitterionic half-sandwich Rhodium(III) and Ruthenium(II) organometallic complexes.

Herein we present the synthesis and characterization of a panel of structurally related zwitterionic piano-stool rhodium(III) and ruthenium(II) complexes. The identities of these novel complexes have been determined by NMR spectroscopy, mass spectrometry, elemental analysis and single-crystal X-ray crystallography. The stability and fluorescence property of these zwitterionic complexes were also confirmed. Zwitterionic rhodium(III) complexes Rh1-Rh4 displayed potent cytotoxic activity against A549 and HeLa human cancer cells. On the contrary, zwitterionic ruthenium(II) complexes Ru1-Ru4 presented no obvious cytotoxic activity to the test cell lines. Moreover, the trend that the introduction of fluorinated substituent and phenyl ring in the η5-CpR ring and N,N-chelating ligand, respectively, could enhance the cytotoxicity of these zwitterionic rhodium(III) complexes, were observed. The exploration of mechanism using flow cytometry displayed that the cytotoxicity of these rhodium(III) complexes was associated with the perturbation of the cell cycle and the induction of cell apoptosis. Furthermore, microscopic analysis using confocal microscopy indicated that the representative rhodium(III) complex Rh4 entered A549 cells via energy-dependent pathway and predominantly accumulated in lysosomes, thus leading to the disruption of lysosomal integrity.

Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching Study.

BACKGROUND: Artificial intelligence (AI) methods can potentially be used to relieve the pressure that the COVID-19 pandemic has exerted on public health. In cases of medical resource shortages caused by the pandemic, changes in people's preferences for AI clinicians and traditional clinicians are worth exploring. OBJECTIVE: We aimed to quantify and compare people's preferences for AI clinicians and traditional clinicians before and during the COVID-19 pandemic, and to assess whether people's preferences were affected by the pressure of pandemic. METHODS: We used the propensity score matching method to match two different groups of respondents with similar demographic characteristics. Respondents were recruited in 2017 and 2020. A total of 2048 respondents (2017: n=1520; 2020: n=528) completed the questionnaire and were included in the analysis. Multinomial logit models and latent class models were used to assess people's preferences for different diagnosis methods. RESULTS: In total, 84.7% (1115/1317) of respondents in the 2017 group and 91.3% (482/528) of respondents in the 2020 group were confident that AI diagnosis methods would outperform human clinician diagnosis methods in the future. Both groups of matched respondents believed that the most important attribute of diagnosis was accuracy, and they preferred to receive combined diagnoses from both AI and human clinicians (2017: odds ratio [OR] 1.645, 95% CI 1.535-1.763; P<.001; 2020: OR 1.513, 95% CI 1.413-1.621; P<.001; reference: clinician diagnoses). The latent class model identified three classes with different attribute priorities. In class 1, preferences for combined diagnoses and accuracy remained constant in 2017 and 2020, and high accuracy (eg, 100% accuracy in 2017: OR 1.357, 95% CI 1.164-1.581) was preferred. In class 2, the matched data from 2017 were similar to those from 2020; combined diagnoses from both AI and human clinicians (2017: OR 1.204, 95% CI 1.039-1.394; P=.011; 2020: OR 2.009, 95% CI 1.826-2.211; P<.001; reference: clinician diagnoses) and an outpatient waiting time of 20 minutes (2017: OR 1.349, 95% CI 1.065-1.708; P<.001; 2020: OR 1.488, 95% CI 1.287-1.721; P<.001; reference: 0 minutes) were consistently preferred. In class 3, the respondents in the 2017 and 2020 groups preferred different diagnosis methods; respondents in the 2017 group preferred clinician diagnoses, whereas respondents in the 2020 group preferred AI diagnoses. In the latent class, which was stratified according to sex, all male and female respondents in the 2017 and 2020 groups believed that accuracy was the most important attribute of diagnosis. CONCLUSIONS: Individuals' preferences for receiving clinical diagnoses from AI and human clinicians were generally unaffected by the pandemic. Respondents believed that accuracy and expense were the most important attributes of diagnosis. These findings can be used to guide policies that are relevant to the development of AI-based health care.

A Novel Model System for Understanding Anticancer Activity of Hypoxia-Activated Prodrugs.

Reports on the comprehensive factors for design considerations of hypoxia-activated prodrugs (HAPs) are rare. We introduced a new model system composed of a series of highly water-soluble HAPs, providing a platform to comprehensively understand the interaction between HAPs and hypoxic biosystems. Specifically, four kinds of new HAPs were designed and synthesized, containing the same biologically active moiety but masked by different bioreductive groups. Our results demonstrated that the activity of the prodrugs was strongly dependent on not only the molecular structure but also the hypoxic tumor microenvironment. We found the presence of a direct linear relationship between cytotoxicity of the HAPs and the reduction potential of whole molecule/oxygen concentration/reductase expression. Moreover, limited blood vasculature in hypoxic regions was also a critical barrier for effective activation of the HAPs. This study offers a comprehensive insight into understanding the design factors required for HAPs.

LncRNA MALAT1 is involved in sevoflurane-induced neurotoxicity in developing rats.

OBJECTIVE: The purpose of this study is to uncover the effects of long chain noncoding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) on sevoflurane-induced neurotoxicity in developing rats. METHODS: Sevoflurane neurotoxicity model was established by sevoflurane treatment in 7-day-old Sprague-Dawley rats. The rats were treated with Sevo or MALAT1 small interfering RNA to detect the MALAT1 expression, pathological change, ultrastructure, neuronal apoptosis, expression of apoptosis-related proteins, expression of neurotrophic factors BDNF and NGF, spatial learning and memory function change, as well as neuron cell density of hippocampal tissues. RESULTS: MALAT1 was highly expressed in hippocampus tissues of rats. Downregulation of MALAT1 alleviated the pathological change, improved the ultrastructure, inhibited apoptosis of neuronal cells, declined caspase 3 and Bax while elevated Bcl-2, BDNF and NGF, improved capability of spatial learning and memory, and increased density of hippocampal neurons in hippocampal tissues of sevoflurane-induced rats. CONCLUSION: Suppression of MALAT1 can reduce the apoptosis of hippocampal neurons induced by sevoflurane anesthesia, improve the capability of spatial learning, and memory function and alleviate the loss of hippocampal nerve cells in developing rats. To a certain extent, it plays the role of protecting brain nerve cells.

Downregulation of microRNA-155 stimulates sevoflurane-mediated cardioprotection against myocardial ischemia/reperfusion injury by binding to SIRT1 in mice.

OBJECTIVE: The inhaled sevoflurane has been demonstrated to protect against myocardial ischemia/reperfusion (I/R) injury. However, the relative mechanisms of sevoflurane-mediated cardioprotection remain largely unknown. This study intends to explore the effect of miR-155 on the sevoflurane-mediated cardioprotection by regulating Sirtuin 1 (SIRT1) in mouse models of myocardial I/R. METHODS: Left anterior descending coronary artery ligation was used to induce models of myocardial I/R in mice. The I/R mice were treated with sevoflurane, sevoflurane + mimics negative control (NC) or sevoflurane + miR-155 mimics. The expression of microRNA-155 (miR-155) and SIRT1 was examined by quantitative real-time polymerase chain reaction and Western blot assay. Then cardiac functions and hemodynamic alterations were evaluated. Evans blue-2,3,5-triphenyltetrazolium chloride and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling assay staining methods were adopted to evaluate infarct size and cardiomyocyte apoptosis, respectively. RESULTS: In the I/R mice, miR-155 was expressed at a high level and SIRT1 at a low level. SIRT1 was confirmed to be a target gene of miR-155. The treatment of sevoflurane could reduce miR-155 expression and increased SIRT1 expression in the myocardial tissues, under which conditions, cardiac functions were promoted, accompanied by reduced infarct size and inhibited cardiomyocyte apoptosis. In response to miR-155 upregulation, the sevoflurane-treated I/R mice showed reduced cardiac functions, and increased infarct size and cardiomyocyte apoptosis. CONCLUSION: The findings obtained in this study provide evidence suggesting that miR-155 targets and negatively regulates SIRT1 expression, a mechanism by which the protection of sevoflurane is inhibited against myocardial I/R in mice.

Anti-myocardial Ischemia Effect and Components of Litchi Pericarp Extracts.

Litchi (Litchi chinensis Sonn.) is a famous fruit in south China, and it is also effective for chest tightness or chest pain, irritability, flatulence, epigastric pain and neuralgic pain, hernia pain and testicular swelling, cough, etc. It is valued because a great amount of polyphenol was found in litchi pericarp. In this paper, we got litchi pericarp pure extract by a simple purification method, then evaluated its activity to clear oxygen free radicals in vitro, and evaluated its myocardial protection effect in vivo through acute myocardial ischemia rat model. The results showed that the pure extract had protective effect on myocardial ischemia injury in a certain dose-effect relationship, which reflected in the electrocardiogram, myocardial pathological morphology and other indicators such as cardiac function enzymes, serum and myocardial antioxidant capacity, and eNOS, Bcl-2 and Bax gene expression. Furthermore, we analyzed the components of pure extract by UPLC-MS, ESI-MS and NMR. The main components of PLPE were procyanidin which were identified as procyanidin B2(1), (-)-epicatechin(2), epicatechin-(4ߠ→ 8,2ߠ→ O â†’ 7)-epicatechin-(4ߠ→ 8)-epicatechin(3), A-type procyanidin trimer(4), B-type procyanidin dimer(5) and procyanidin A2(6).This study proved that litchi pericarp extract may have antioxidant activity and cardioprotection effect. It suggested that litchi pericarp may be good for cardiovascular disease. Copyright © 2017 John Wiley & Sons, Ltd.

Discrimination of botanical origins for Chinese honey according to free amino acids content by high-performance liquid chromatography with fluorescence detection with chemometric approaches.

BACKGROUND: The contents of 18 free amino acids in 87 Chinese honey samples from four botanical origins (linden, acacia, vitex and rape) were determined by developing a high-performance liquid chromatography with fluorescence detector (HPLC-FLD) method with an in-loop automated pre-column derivatization. The free amino acid profiles of these samples were used to construct a statistical model to distinguish honeys from various floral origins. RESULTS: The average contents of all free amino acids in linden honey were lower than in the other three types of honey. Phenylalanine was particularly useful in the present study because its average content in vitex honey was far higher than in any other honey samples. There is no doubt that both phenylalanine and tyrosine can be considered as the marker free amino acid in Chinese vitex honey. Principal component analysis (PCA) was conducted based on 15 free amino acids and showed significant differences among the honey samples. The cumulative variance for the first two components was 80.62%, and the four principal components can explain 94.18% of the total variance. In the two first component scores, the honey samples can be separated according to their botanical origins. Cluster analysis of amino acid data also revealed that the botanical origins of honey samples correlated with their amino acid content. Back-propagation artificial neural network (BP-ANN) and naïve Bayes methods were employed to construct the classification models. The results revealed an excellent separation among honey samples according to their botanical origin with 100% accuracy in model training for both BP-ANN and naïve Bayes. CONCLUSION: It indicated that the free amino acid profile determined by HPLC-FLD can provide sufficient information to discriminate honey samples according to their botanical origins. © 2016 Society of Chemical Industry.

Evaluation of three pumpkin species: correlation with physicochemical, antioxidant properties and classification using SPME-GC-MS and E-nose methods.

To ascertain the most discriminant variables for three pumpkin species principal component analysis (PCA) was performed. Twenty-four parameters (pH, conductivity, sucrose, glucose, total soluble solids, L*, a*, b*, individual weight, edible rate, firmness, citric acid, fumaric acid, l-ascorbic acid, malic acid, PPO activity, POD activity, total flavonoids, vitamin E, total phenolics, DPPH, FRAP, ß-carotene, and aroma) were considered. The studied pumpkin species were Cucurbita maxima, Cucurbita moschata, and Cucurbita pepo. Three pumpkin species were classified by PCA based on aroma, physicochemical and antioxidant properties because the sum of PC1 and PC2 were both greater than 85% (85.06 and 93.64% respectively). Results were validated by the PCA and showed that PPO activity, total flavonoid, sucrose, glucose, TSS, a*, pH, malic acid, vitamin E, DPPH, FRAP and ß-carotene, and aroma are highly useful parameters to classify pumpkin species.

High-Throughput Analytical Techniques for Determination of Residues of 653 Multiclass Pesticides and Chemical Pollutants in Tea--Part V: A Comparative Study of the Influence of Tea Hydration on the Efficiency of Pesticide Multiresidue Determination Using Three Sample Preparation Methods and GC/MS/MS.

This paper describes a comparative study of the influence of three sample preparation techniques (M1: hydration+oscillating extraction+partial extraction solution hexane partitioning cleanup; M2: hydration+oscillating extraction+overall extraction solution SPE cleanup; and M3: pure acetonitrile homogeneous extraction+overall extraction SPE cleanup) on the determination efficiency of 456 pesticide multiresidues in tea. First, it was discovered from the mathematical correlation equation of 329 pesticide recoveries established and log Kow values that the extraction efficiency of hydration method M1 has obvious correlation with pesticide log Kow, making the extraction efficiency of M1 take the shape of an arc trend line with a certain arc hanging down from both ends of polar pesticides and nonpolar pesticides. Second, regarding the M1 method, the interfering matter after co-extraction increased in large quantities, which markedly lowered the S/N of the target pesticides and method sensitivity, leading to an obvious decrease of the method efficiency. The fortification experiment of the uniform limit 0.010 mg/kg proved that with the M1 hydration method there are 23 pesticides with recoveries between 70 and 120% and RSD<20%, accounting for only 5.0%, while with nonhydration method M3 there are 229 pesticides, making up 50%.

[Application of ICP-MS method in the determination of mineral elements in vitex honey for the classification of their geographical origins with chemometric approach].

In the present work, the contents of 38 elements of 65 vitex (Vitex negundo var. heterophylla Rehd. ) honey samples from Shunyi of Beijing, Fuping and Pingshan of Hebei province were determined by inductively coupled plasma mass spectrometry (ICP-MS). Among them, B, Na, Mg, P, K, Ca, Fe and Zn were the most abundant elements with mean contents more than 1 mg kg-1. It can be found that there were relationships between the contents of elements and the geographical origin of vitex honey samples. Taking the contents of 29 out of 38 mineral elements (Na, Mg, Al, K, Ti, V, Mn, Fe, Ni, Cu, Zn, Ga, As, Sr, Y, Mo, Cd, Ba, La, Ce, Pr, Nd, Sm, Gd, Dy, Ho, T1, Pb and U) as variables, the chemometric methods, such as principal component analysis (PCA) and back-propagation artificial neural network (BP-ANN), were applied to classify vitex honey samples according to their geographical origins. PCA reduced all of the variables to four principal components and could explain 81. 6% of the total variances. The results indicated that PCA could mainly classify the vitex honey samples into three groups. BP-ANN was explored to construct classification model of vitex honeys according to their geographical origin. For the whole data set, the overall correct classification rate and cross-validation (leave one out method) rate of proposed BP-ANN model was 100% and 95. 4%, respectively. To further test the stability of the model developed for prediction, 75% of honey samples of each geographical origin were randomly selected for the model training set, and the remaining samples were classified with the use of the constructed model. Both the overall correct classification rate and prediction rate of proposed BP-ANN model were 100%. It is concluded that the profiles of multi-element by ICP-MS with chemometric methods could be a potential and powerful tool for the classification of vitex honey samples from different geographical origins.

The fate of enterohemorrhagic Escherichia coli on alfalfa and fenugreek seeds and sprouts as affected by ascaroside #18 treatments.

Alfalfa and fenugreek sprouts are healthy foods, but they are occasionally contaminated with bacterial pathogens and serve as vehicles for transmitting foodborne illnesses. This study examined the efficacy of ascaroside (ascr)#18 treatment for the control of enterohemorrhagic E. coli (EHEC) growth on sprouts. Commercial alfalfa and fenugreek seeds were decontaminated with 20,000 ppm of NaClO, and residual chlorine was neutralized with Dey-Engley broth. Decontaminated seeds were treated with 1 mM or 1 µM ascr#18, a plant immunity modulator, before being dried and mixed with sandy soil inoculated with E. coli F4546 or BAA-2326 at 104-105 CFU/g. The inoculated seeds were sprouted on 1% water agar at 25ºC for 7 days in the dark. Seed or sprout samples were collected on days 0, 1, 3, 5, and 7 for enumeration of bacterial populations. Data was fit into the general linear model and analyzed using Fisher's least significant different test of the statistical analysis software. Treatment with ascr#18 significantly (P ≤ 0.05) reduced the cell population of EHEC on sprouts. The mean EHEC populations in the 1 mM or 1 µM treatment groups were 3.31 or 1.56 log CFU/g lower compared to the control groups. Besides treatment, sprout seed type and sprouting time were also significant independent variables influencing the growth of EHEC, according to the results of type III error analysis. However, EHEC strain type was not a significant independent variable. The study suggests that ascr#18 could be potentially used to control EHEC contamination and improve the microbial safety of sprouts.

Influence of ultrasound on the microbiological, physicochemical properties, and sensory quality of different varieties of pumpkin juice.

This study has investigated the effect of ultrasound (US) as an emerging non-thermal sterilization technique on microbial growth and quality changes in three freshly squeezed pumpkin juices (Cucurbita maxima Duchesne, Cucurbita moschata Duchesne, and Cucurbita pepo L.).The three pumpkin juices were ultrasonicated at different ultrasonic power (0-400 W), time (0-20 min), and temperature (0-30 °C), and the total colony counts of the treated pumpkin juices were less than 5 log CFU/mL, which complied with the food safety and consumption standards. Based on these results, we further investigated the effects of different ultrasonic power (25 kHz, 10 min, 20 °C, 0-400 W) on the physicochemical properties and sensory quality of the three pumpkin juices. The physicochemical properties (color, sugar content, organic acid content, soluble solids, and carotenoids) of treated pumpkin juice were retained or improved to some extent. The antioxidant capacity was also increased by 9.09%, 10.25%, and 16.9% compared to the untreated group. During sonication, the particle size of all samples decreased significantly, the microstructure broke down significantly, and the sensory qualities of pumpkin juice were well preserved after sonication.

Unraveling the dynamic transcriptomic changes during the dimorphic transition of Talaromyces marneffei through time-course analysis.

Introduction: Systemic dimorphic fungi pose a significant public health challenge, causing over one million new infections annually. The dimorphic transition between saprophytic mycelia and pathogenic yeasts is strongly associated with the pathogenesis of dimorphic fungi. However, despite the dynamic nature of dimorphic transition, the current omics studies focused on dimorphic transition primarily employ static strategies, partly due to the lack of suitable dynamic analytical methods. Methods: We conducted time-course transcriptional profiling during the dimorphic transition of Talaromyces marneffei, a model organism for thermally dimorphic fungi. To capture non-uniform and nonlinear transcriptional changes, we developed DyGAM-NS (dynamic optimized generalized additive model with natural cubic smoothing). The performance of DyGAM-NS was evaluated by comparison with seven other commonly used time-course analysis methods. Based on dimorphic transition induced genes (DTIGs) identified by DyGAM-NS, cluster analysis was utilized to discern distinct gene expression patterns throughout dimorphic transitions of T. marneffei. Simultaneously, a gene expression regulatory network was constructed to probe pivotal regulatory elements governing the dimorphic transitions. Results: By using DyGAM-NS, model, we identified 5,223 DTIGs of T. marneffei. Notably, the DyGAM-NS model showcases performance on par with or superior to other commonly used models, achieving the highest F1 score in our assessment. Moreover, the DyGAM-NS model also demonstrates potential in predicting gene expression levels throughout temporal processes. The cluster analysis of DTIGs suggests divergent gene expression patterns between mycelium-to-yeast and yeast-to-mycelium transitions, indicating the asymmetrical nature of two transition directions. Additionally, leveraging the identified DTIGs, we constructed a regulatory network for the dimorphic transition and identified two zinc finger-containing transcription factors that potentially regulate dimorphic transition in T. marneffei. Discussion: Our study elucidates the dynamic transcriptional profile changes during the dimorphic transition of T. marneffei. Furthermore, it offers a novel perspective for unraveling the underlying mechanisms of fungal dimorphism, emphasizing the importance of dynamic analytical methods in understanding complex biological processes.