Vitamin D Deficiency Exacerbates Poor Sleep Outcomes with Endocrine-Disrupting Chemicals Exposure: A Large American Population Study.

Phthalates and bisphenol A are recognized as the predominant endocrine-disrupting substances (EDCs) in the environment, but their impact on sleep health remains unclear. Vitamin D has often been reported to play a role in sleep health and may be affected by endocrine-disrupting compounds. The study utilized data from 5476 individuals in the NHANES project to investigate the correlation between combined exposure to environmental EDCs and sleep duration through modeling various exposures. Furthermore, it emphasizes the importance of vitamin D in the present scenario. Preliminary analyses suggested that vitamin D-deficient individuals generally slept shorter than individuals with normal vitamin D (p < 0.05). Exposure to Mono-ethyl phthalate (MEP), triclosan (TRS), and Mono-benzyl phthalate (MZP), either alone or in combination, was associated with reduced sleep duration and a greater risk of vitamin D deficiency. Individuals with low vitamin D levels exposed to TRS experienced shorter sleep duration than those with normal vitamin D levels (p < 0.05). TRS and MZP were identified as crucial factors in patient outcomes when evaluating mixed exposures (p < 0.05). The results provide new data supporting a link between exposure to EDCs and insufficient sleep length. Additionally, they imply that a vitamin D shortage may worsen the sleep problems induced by EDCs.

A colorimetric sensor based on 4-MPBA Au@AgNPs for accurately identification of EnshiYulu tea grade.

Enshi Yulu green tea (ESYL) is the most representative traditional steamed green tea in Enshi, Hubei. Different ESYL grades exhibit distinct flavors, tastes, and prices. In this study, a visual sensor based on 4-MPBA Au@AgNPs was developed for the rapid and accurate identification of ESYL grades. The recognition mechanism involved the binding of 4-MPBA Au@AgNPs with polyphenolic compounds in ESYL to form borate esters and the conversion of Ag+ to Ag0, with the generated Ag0 depositing on the surface of 4-MPBA Au@AgNPs. The results showed that the sensor can amplify the color differences of different grades of ESYL. The visual results were also validated by the partial least squares discriminant analysis model, demonstrating an enhancement in recognition accuracy from 68.2 % to 95.5 % compared to the original extraction solution. The colorimetric sensor developed in this study is expected to provide a new approach for traceability research of other foods.

The Correlation between Metal Mixed Exposure and Lung Function in Different Ages of the Population.

Herein, we explored the overall association between metal mixtures and lung functions in populations of varying ages and the relationship among the associated components. The 2007-2012 National Health and Nutrition Examination Survey data of 4382 American participants was analyzed, and generalized linear, elastic net, quantile g-computation, and Bayesian kernel machine regression models were used to evaluate the relationship between exposure to the metal mixture and lung function at various ages. The results of barium exposure at distinct stages revealed that children and adolescents exhibited greater lung function changes than those in adults and the elderly. Additionally, compared with children and adolescents, cadmium- and arsenic-containing metabolites contributed to nonconductive lung function changes in adults and the elderly exposed to metal mixtures. The results showed that the effects of exposure to metal mixtures on lung function in children and adolescents were predominantly caused by lead and barium. Altogether, children and adolescents were found to be more susceptible to metal-exposure-mediated lung function changes than adults and the elderly.

Zinc Oxide Nanoparticles Exacerbate Epileptic Seizures by Modulating the TLR4-Autophagy Axis.

Background: Zinc oxide nanoparticles (ZnO NPs) has been widely used in various fields and has had an important impact on human public health. In addition, it inevitably damages human health, including neurological diseases. Therefore, this study explored the effect of ZnO NPs on epilepsy. Methods: The effect of ZnO NPs on epilepsy was observed by behavioral analysis. TLR4 expression and autophagy related pathways were detected by RNA-seq and Western blot. In addition, the cell types of autophagy were detected by immunofluorescence. Further, the electrophysiological changes of ZnO NPs induced autophagy were detected by whole-cell patch-clamp. Finally, the recovery experiment was carried out by TLR4 inhibitor (TAK-242). Results: We found that ZnO NPs enhanced epilepsy susceptibility and severity. Through RNA-seq analysis and Western blot, it was found that ZnO NPs affected the changes of TLR4 and autophagy related pathways. In addition, we found that ZnO NPs mainly affects autophagy of inhibitory neurons, resulting in excitation/inhibition imbalance. The autophagy and epileptic phenotypes were reversed with TAK-242. In general, ZnO NPs exacerbate epileptic seizures by modulating the TLR4-autophagy axis. Conclusion: ZnO NPs enhanced the susceptibility and severity of epilepsy. Mechanistically, ZnO NPs affected autophagy by changing the expression of TLR4. In particular, the ZnO NPs mainly affected the synaptic function of inhibitory neuron, leading to excitation/inhibition imbalances.

Discrimination and prediction of Qingzhuan tea storage year using quantitative chemical profile combined with multivariate analysis: Advantages of MRMHR based targeted quantification metabolomics.

The duration of storage significantly influences the quality and market value of Qingzhuan tea (QZT). Herein, a high-resolution multiple reaction monitoring (MRMHR) quantitative method for markers of QZT storage year was developed. Quantitative data alongside multivariate analysis were employed to discriminate and predict the storage year of QZT. Furthermore, the content of the main biochemical ingredients, catechins and alkaloids, and free amino acids (FAA) were assessed for this purpose. The results show that targeted marker-based models exhibited superior discrimination and prediction performance among four datasets. The R2Xcum, R2Ycum and Q2cum of orthogonal projection to latent structure-discriminant analysis discrimination model were close to 1. The correlation coefficient (R2) and the root mean square error of prediction of the QZT storage year prediction model were 0.9906 and 0.63, respectively. This study provides valuable insights into tea storage quality and highlights the potential application of targeted markers in food quality evaluation.

UHPLC-QTOF-MS-based untargeted metabolomic authentication of Chinese red wines according to their grape varieties.

Wine is a very popular alcoholic drink owing to its health benefits of antioxidant effects. However, profits-driven frauds of wine especially false declarations of variety frequently occurred in markets. In this work, an UHPLC-QTOF-MS-based untargeted metabolomics method was developed for metabolite profiling of 119 bottles of Chinese red wines from four varieties (Cabernet Sauvignon, Merlot, Cabernet Gernischt, and Pinot Noir). The metabolites of red wines from different varieties were assessed using orthogonal partial least-squares discriminant analysis (OPLS-DA) and analyzed using KEGG metabolic pathway analysis. Results showed that the differential compounds among different varieties of red wines are mainly flavonoids, phenols, indoles and amino acids. The KEGG metabolic pathway analysis showed that indoles metabolism and flavonoids metabolism are closely related to wine varieties. Based on the differential compounds, OPLS-DA models could identify external validation wine samples with a total correct rate of 90.9 % in positive ionization mode and 100 % in negative ionization mode. This study indicated that the developed untargeted metabolomics method based on UHPLC-QTOF-MS is a potential tool to identify the varieties of Chinese red wines.

Third-order calibration applied to process surfactant-modulated excitation-emission matrix four-way fluorescence data for the direct determination of four polycyclic aromatic hydrocarbons in oilfield produced water.

Fluorescence spectroscopy is a powerful tool to determine polycyclic aromatic hydrocarbons (PAHs) owing to the strong endogenous fluorescence of these compounds. However, the presence of unknown interferences and overlapped spectra hinders the accurate determination of PAHs in oilfield produced water. Moreover, surfactants frequently coexist in oilfield produced water and will seriously affect the fluorescence signals of PAHs. Herein, a new methodology applying third-order calibration to process four-way (4D) fluorescence data was proposed to solve these problems and achieve accurate determination of pyrene, fluorene, phenanthrene, and fluoranthene as an example in oilfield produced water. The methodology is based on excitation-emission matrix fluorescence modulated by different concentrations of sodium dodecyl benzene sulfonate (SDBS) in the analyzed samples. The 4D fluorescence data were processed by third-order calibration methods including four-way parallel factor analysis (4-PARAFAC) and alternating weighted residue constraint quadrilinear decomposition (AWRCQLD), and the results were compared with those of second-order calibration methods. It was proved that third-order calibration was capable of accurately identifying and quantifying PAHs together with SDBS in oilfield produced water, which has better quantitative results and figures of merit compared to second-order calibration. This study provided a new approach to generating 4D fluorescence data and opened up an avenue for the accurate determination of PAHs in complex oilfield produced water with surfactants.

Revealing the chemical differences and their application in the storage year prediction of Qingzhuan tea by SWATH-MS based metabolomics analysis.

It's generally believed that the longer the storage, the better the quality of dark tea, but the chemical differences of Qingzhuan tea (QZT) with different storage years is still unclear. Herein, in this work, an untargeted metabolomic approach based on SWATH-MS was established to investigate the differential compounds of QZT with 0-9 years' storage time. These QZT samples were roughly divided into two categories by principal component analysis (PCA). After orthogonal projections to latent structures discriminant analysis (OPLS-DA), 18 differential compounds were putatively identified as chemical markers for the storage year variation of QZT. Heatmap visualization showed that the contents of catechins, fatty acids, and some phenolic acids significantly reduced, flavonoid glycosides, triterpenoids, and 8-C N-ethyl-2-pyrrolidinone-substituted flavan-3-ols (EPSFs) increased with the increase of storage time. Furthermore, these chemical markers were verified by the peak areas corresponding to MS2 ions from SWATH-MS. Based on the extraction chromatographic peak areas of MS and MS2 ions, a duration time prediction model was built for QZT with correlation coefficient R2 of 0.9080 and 0.9701, and RMSEP value of 0.85 and 1.24, respectively. This study reveals the chemical differences of QZT with different storage years and provides a theoretical basis for the quality evaluation of stored dark tea.

A comprehensive review of the current trends and recent advancements on the authenticity of honey.

The authenticity of honey currently poses challenges to food quality control, thus requiring continuous modernization and improvement of related analytical methodologies. This review provides a comprehensively overview of honey authenticity challenges and related analytical methods. Firstly, direct and indirect methods of honey adulteration were described in detail, commenting the existing challenges in current detection methods and market supervision approaches. As an important part, the integrated metabolomic workflow involving sample processing procedures, instrumental analysis techniques, and chemometric tools in honey authenticity studies were discussed, with a focus on their advantages, disadvantages, and scopes. Among them, various improved microscale extraction methods, combined with hyphenated instrumental analysis techniques and chemometric data processing tools, have broad application potential in honey authenticity research. The future of honey authenticity determination will involve the use of simplified and portable methods, which will enable on-site rapid detection and transfer detection technologies from the laboratory to the industry.

Target-switched artificial biochemical circuit for a versatile and sensitive colorimetric detection platform.

The presence of the target causes the structural switch of a metastable hairpin template probe (MH) for triggering a self-primed artificial biochemical circuit to produce numerous DNAzyme replicates, which in turn results in substantial signal amplification for highly sensitive colorimetric determination of nucleic acids.

A Comprehensive Review on the Excitation-Emission Matrix Fluorescence Spectroscopic Characterization of Petroleum-Containing Substances: Principles, Methods, and Applications.

Petroleum-containing substance (PCS) is a general term used for petroleum and its derivatives. A comprehensive characterization of PCSs is crucial for resource exploitation, economic development and environmental protection. Fluorescence spectroscopy, especially excitation-emission matrix fluorescence (EEMF) spectroscopy, has been proved to be a powerful tool to characterize PCSs since its remarkable sensitivity, selectivity, simplicity and high efficiency. However, there is a lack of systematic review focusing on this field in the literature. This paper reviews the fundamental principles and measurements of EEMF for characterizing PCSs, and makes a systematic introduction to various information mining methods including basic peak information extraction, spectral parameterization and some commonly used chemometric methods. In addition, recent advances in applying EEMF to characterize PCSs during the whole life-cycle process of petroleum are also revisited. Furthermore, the current limitations of EEMF in the measurement and characterization of PCSs are discussed and corresponding solutions are provided. For promoting the future development of this field, the urgent need to build a relatively complete EEMF fingerprint library to trace PCSs, not only pollutants but also crude oil and petroleum products, is proposed. Finally, the extensions of EEMF to high-dimensional chemometrics and deep learning are prospected, with the expectation of solving more complex systems and problems.

The association of cortisol/testosterone ratio and sleep quality with coronary heart disease: A case-control study in Chinese rural population.

PURPOSE: There were limited studies that have probed into the combined effect of the cortisol/testosterone (C/T) ratio as a biomarker of stress and Pittsburgh Sleep Quality Index (PSQI) on coronary heart disease (CHD). This research aimed to explore the association of C/T ratio and PSQI with the risk of CHD in a rural Chinese population, as well as the interaction and combined effect between C/T ratio and PSQI on CHD. METHODS: A case-control study was performed including 307 individuals without CHD and 307 patients drawn from Henan Rural Cohort. Logistic regression was utilized to survey the independent and joint effects of the C/T ratio and PSQI on CHD. To estimate the interaction impact of the C/T ratio and sleep quality (PSQI) on CHD, a cross-product term was introduced in the generalized linear model. RESULTS: Higher C/T ratio and PSQI index scores are related to increased odds ratio for CHD (Odds ratios (ORs) and 95 % confidence interval (CI) were 1.17 (1.07, 1.29), p-trend < 0.001; 1.16 (1.09, 1.22), respectively). The odds ratio of C/T ratio for CHD increased with increasing PSQI in women (pinteraction = 0.018) and total population (pinteraction = 0.033). The combined group of high C/T ratio and high PSQI had the highest risk of CHD (Total: OR = 7.53, 95 % CI: 4.12-13.76). CONCLUSIONS: The risk of CHD was associated with low testosterone levels, high C/T ratios, and high PSQI scores. Additionally, poor sleep quality aggravated the effect of high C/T ratio on coronary heart disease.

UHPLC-QTOF-MS-based untargeted metabolomics and mineral element analysis insight into the geographical differences of Chrysanthemum morifolium Ramat cv. "Hangbaiju" from different origins.

Chrysanthemum morifolium Ramat cv. "Hangbaiju" (HBJ), known as one of the "eight flavors of Zhejiang", is commonly used as a classical tea material for both food and medicine over three thousand years in China. The quality of HBJ is closely related to its geographical origins. However, the mechanism underlying the geographical differences of HBJ remains to be elucidated. In this study, an untargeted metabolomic strategy based on UHPLC-QTOF-MS was established to discover the differential metabolites in HBJ samples from four different origins and explore the possible relationship with mineral elements in planting soils by chemometric analysis. Eight compounds were screened and identified as the key differential metabolites in HBJ samples from different origins. Among them, four important pharmacodynamic compounds including L-arginine, rutin, chlorogenic acid and apigenin-7-O-glucoside are the most abundant in HBJ samples from Tongxiang region, which suggests that HBJ planted in Tongxiang has higher medicinal values. Pearson correlation analysis revealed that the contents of soil mineral elements are positively correlated with those of chlorogenic acid, rutin, apigenin-7-O-glucoside in HBJ samples. Furthermore, an interrelationship model based on random forest algorithm was established to successfully predict the contents of differential metabolites in HBJ samples by soil mineral elements. All these results indicated that the contents of differential metabolites in HBJ samples seemed to be affected by soil mineral elements and therefore resulted in the geographical differences of HBJ.

Effects of combination therapy with Shenfu Injection in critically ill patients with septic shock receiving mechanical ventilation: A multicentric, real-world study.

Background: Septic shock has increasingly become a cause of death threatening human survival. Shenfu Injection (SFI), a patented Chinese medicine, has been widely used in the treatment of patients with sepsis and cardiovascular diseases domestically. We sought to examine whether combination therapy with SFI can improve clinical outcomes in critically ill patients undergoing mechanical ventilation (MV). Methods: This real-world, multicenter retrospective trial enrolled consecutive adult patients with sepsis requiring MV from four medical/surgical intensive care units (ICUs) in China between August 2016 and September 2021. Patients were identified from the medical information department database of each center and assigned to either of two groups (SFI or control) on the basis of the initial treatment received. The primary outcome was 28-day all-cause mortality, and the durations of vasopressor therapy and MV, the ICU length of stay, and costs were assessed as secondary outcomes. Subsequently, we performed a meta-analysis of randomized controlled trials (RCTs) on SFI published before July 2021 to verify our conclusions. Results: 2311 mechanically ventilated patients with septic shock (1128 patients in the SFI group and 1183 in the control group) were analyzed. The survival probability during the first 28 days after admission in the SFI group was greater than that in the control group [p < 0.01 by log-rank test; hazard ratio (HR), 0.56; 95% confidence interval (CI), 0.39-0.72]. Patients in the SFI group also experienced a significantly reduced duration of vasopressor therapy [7.28 (95% CI, 6.14-8.42) vs. 12.06 (95% CI, 10.71-13.41) days, p < 0.001], more ventilator-free days [6.49 (95% CI, 5.42-7.55) vs. 10.84 (95% CI, 9.59-12.09) days, p < 0.001], a shorter ICU length of stay [18.48 (95% CI, 17.59-19.38) vs. 23.77 (95% CI, 22.47-25.07) days, p < 0.001], and more time free from organ failure [14.23 (95% CI, 12.94-15.52) vs. 19.07 (95% CI, 16.09-22.05) days, p < 0.001]. No major adverse effects were reported in either group. Conclusion: Among critically ill patients requiring MV, combination therapy with SFI can improve the survival probability without any obvious adverse reactions.

Tracing sources of oilfield wastewater based on excitation-emission matrix fluorescence spectroscopy coupled with chemical pattern recognition techniques.

In order to prevent the illegal discharge of oilfield wastewater, this work proposed excitation-emission matrix fluorescence (EEMF) spectroscopy coupled with two kinds of chemical pattern recognition methods for tracing the sources of oilfield wastewater. The first pattern recognition method was built from the relative concentrations extracted by alternating trilinear decomposition (ATLD) based on partial least squares-discriminant analysis (PLS-DA) algorithm, and the other one was modeled based on strictly multi-way partial least squares-discriminant analysis (N-PLS-DA). Both methods showed good discrimination abilities for oilfield wastewater samples from three different sources. The total recognition rates of the training and prediction sets are 100%, the values of sensitivity and selectivity are 1. This study showed that EEMF spectroscopy combined with chemical pattern recognition techniques could be used as a potential tool for tracing the sources of oilfield wastewater.

Untargeted metabolomic analysis of Chinese red wines for geographical origin traceability by UPLC-QTOF-MS coupled with chemometrics.

Identifying geographical origins of red wines made in specific regions is of significance since the false claim of geographical origins has been frequently exposed in China's wine industry. In this work, an untargeted metabolomic approach based on UPLC-QTOF-MS was established to discriminate geographical origins of Chinese red wines. The principal component analysis (PCA) showed significant differences between wine samples from three famous geographical origins in China. The metabolites contributing to the differentiation were screened by orthogonal partial least squares-discriminant analysis (OPLS-DA) with pairwise modeling. 40 and 46 differential metabolites in positive and negative ionization modes were putatively identified as chemical markers. Furthermore, heatmap visualization and OPLS-DA models were constructed based on these identified markers and external verification wine samples from different regions were successfully discriminated, with recognition rate up to 96.7%. This study indicated that UPLC-QTOF-MS-based untargeted metabolomics has great potential for the geographical origin traceability of Chinese red wines.

Highly fluorescent N doped C-dots as sensor for selective detection of Hg2+ in beverages.

In this work, nitrogen doped carbon dots (NCDs) were synthesized through one step hydrothermal reaction using citric acid and ethylenediamine as precursors. The prepared NCDs exhibit high quantum yield of 67.4%, good stability, excellent selectivity and sensitivity. It was found that the NCDs have potential as a fluorescence sensor for the detection of Hg2+. Under optimal conditions, good linearity between the change in NCDs fluorescence intensity and Hg2+ concentration was obtained in the range of 0.3 to 2.0 µM with a detection limit at 0.24 µM. The possible detection mechanism was static quenching of NCDs by Hg2+. The established method was successfully applied to the determination of Hg2+ in beverage samples. The results indicated that the NCDs-based sensor has potential for detection of Hg2+ in real beverage sample.

Target-induced activation of DNAzyme for sensitive detection of bleomycin by using a simple MOF-modified electrode.

In this work, a sensitive electrochemical method for bleomycin (BLM) determination was reported on the basis of BLM-mediated activation of Zn2+-dependent DNAzyme and the adsorption of signal probes by a metal-organic framework (MOF) modified electrode. Two hairpin DNAs were employed in this protocol, one (HP1) for BLM recognition and one (HP2) for amplified signal output. The presence of BLM and Fe2+ caused the formation of BLM-Fe (II) complex to cleave HP1, releasing DNAzyme fragments, which could further hybridize with substrate HP2 to form a partial double-stranded DNA duplex and enable the activation of Zn2+-dependent DNAzyme with the coexistence of Zn2+. The Zn2+-dependent DNAzyme catalyzed the cyclic cleavage of magnetic beads (MB)-immobilized HP2 to release massive DNA fragments with a Fc-labeled- terminal, which could be used for BLM quantification through electrochemical measurement after their adsorption on a MOF modified electrode. Attributing to the high catalytic efficiency of DNAzyme and excellent electrochemical performance of MOF modified electrode, our method revealed an impressive limit of detection as low as 4 pM BLM with a linear range of 5-2000 pM. Besides, the easy synthesis of MOF without further modification and the easy way of adsorption for signal achievement facilitated the operation process. In virtue of the high sensitivity, selectivity and the simple-to-implement features, this method is believed to hold a great promising application for BLM determination in biomedical and clinical study.

HPLC-DAD fingerprints combined with chemometric techniques for the authentication of plucking seasons of Laoshan green tea.

Laoshan green teas plucked in summer and autumn were measured by high performance liquid chromatography-diode array detector (HPLC-DAD). After baseline correction, the fingerprints data were resolved by multivariate curve resolution-alternating least squares (MCR-ALS) and a total of 57 components were acquired. Relative concentrations of these components were afterwards applied to distinguish plucking seasons using principal component analysis (PCA), support vector machines (SVM) and partial least squares-discriminant analysis (PLS-DA). For both SVM and PLS-DA models, the total recognition rates of training set, cross-validation and testing set were 100%, 91.3% and 100%, respectively. Besides, three variable selection methods were employed to determine characteristic components for the authentication of summer and autumn teas. Results showed that PLS-DA model based on three characteristic components selected by VIP possesses identical predictive ability as the original model. This study demonstrated that our proposed strategy is competent for the authentication of plucking seasons of Laoshan green tea.

Sensitive detection of streptomycin in milk using a hybrid signal enhancement strategy of MOF-based bio-bar code and target recycling.

A MOF-based bio-bar code material was synthesized and firstly applied to develop an electrochemical streptomycin (STR) aptasensor. By using MOF-based bio-bar code and enzyme-assisted target recycling for dual-signal amplification, highly sensitive detection of STR was achieved. The sensing surface was simply fabricated by immobilizing a mixed monolayer of thiolated cDNA/aptamer duplexes (dsDNA) and 6-mercapto-1-hexanol (MCH) on the gold nanoparticle modified screen printed carbon electrode (Au/SPCE). The presence of target STR caused highly efficient removal of the aptamers from dsDNA assisted by Exo I enzyme. Then MOF-based bio-bar codes were backfilled to achieve the adsorption of electroactive Ru(NH3)63+ (RuHex) on electrode surface. The electrochemical signal of the surface-confined RuHex was used for quantitation. The analytical performance for STR was satisfactory with a wide linear range of 0.005-150 ng mL-1, a low detection limit of 2.6 pg mL-1 and a good selectivity towards other three antibiotics. Moreover, the application of this aptasensor for determination of STR in real milk samples was also realized. With these merits, this dual-signal amplification assay might provide one of the effective ways for food safety monitoring.