Objective To establish an ultra-high-performance liquid chromatography-triple quadrupole tandem mass spectrometry method for the determination of N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine quinone (6PPDQ) in human plasma and urine. Methods Plasma and urine samples (0.3 mL each) were mixed with 0.9 mL acetonitrile and dichloromethane, vortexed, and subjected to ultrasonic treatment to facilitate extraction. After centrifugation, the extract was collected, evaporated to dry powder under nitrogen, and reconstituted. Separation was performed on a C18 column, and detection was carried out using ultra-high-performance liquid chromatography-triple quadrupole tandem mass spectrometry with external standard quantification. Results 6PPDQ showed good linearity in the range of 0.01-25.00 μg/L in both human plasma and urine, with correlation coefficients of 0.999 5 and 0.999 7, respectively. The detection limits for plasma and urine were 8 and 6 ng/L, and the lower limits of quantification were 27 and 19 ng/L, respectively. The average recovery rates were 97.00%-100.00% for plasma and 90.00%-96.50% for urine. The within-run relative standard deviations (RSDs) were 4.35%-10.00% for plasma and 2.34%-11.11% for urine, while the between-run RSDs were 6.80%-8.46% and 2.60%-10.00%, respectively. Samples can be stored for seven days at 4 ℃ or -20 ℃. respectively. Samples can be stored for seven days at 4 ℃ or -20 ℃. Matrix effects ranged from 87.12%-99.27% for plasma and 91.00%-97.56% for urine. Conclusion The proposed method is simple, highly sensitive, and reproducible, and is suitable for the determination of 6PPDQ in human plasma and urine samples.

Objective To analyze differential metabolites (DMs) in the urine of workers with occupational nickel exposure using non-targeted metabolomics, and to screen differential metabolic pathways. Methods A total of 30 nickel exposed workers were selected as the exposure group, and 30 administrative staff from the same factory were selected as the control group using the judgment sampling method. Urine samples of the individuals from the two groups were collected. The ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry and non-targeted metabolomics were used to detect and identify metabolites. The differential metabolic profiles were compared between workers of the two groups, and key differential metabolic pathways and potential biomarkers were screened. The association of DMs and urinary nickel level were evaluated by Spearman correlation coefficients. The sensitivity and specificity of biomarkers were assessed by receiver operating characteristic (ROC) curve analysis. Results A total of 418 metabolites were identified in the urine of worker in the exposure and control groups. The result of principal component analysis and orthogonal partial least squares analysis showed that there were 128 DMs in the urine of workers in the exposure group compared with the control group. These DMs were mainly enriched in glutathione metabolism, carnitine synthesis, and amino acid and nucleotide metabolism pathways, including glycine and serine metabolism. The result of correlation analysis and ROC curve analysis revealed that 4-methylcatechol, 4-vinylphenol sulfate, 2-hydroxyphenylacetone sulfate, 2-dodecylbenzenesulfonic acid, and decylbenzenesulfonic acid could be the potential biomarkers for nickel exposure (all area under the ROC curve >0.800). Conclusion There were significant differences in the urinary metabolic profiles of workers with occupational nickel exposure. The five DMs including 4-methylcatechol, 4-vinylphenol sulfate, 2-hydroxyphenylacetone sulfate, 2-dodecylbenzenesulfonic acid, and decylbenzenesulfonic acid. These DMs could be potential biomarkers of occupational nickel exposure.

Biotoxins, which include bacterial, fungal, marine, plant, and animal toxins, are widespread in living and occupational environments, posing potential threats to human health. Rapid detection of biotoxins in blood is crucial for preventing health hazards and enabling timely disease diagnosis and treatment. Biosensors and immunoassay technologies have critical advantages in the rapid detection of biotoxins in blood. Common biosensors, such as surface plasmon resonance biosensors and fluorescent biosensors, enhance sensitivity and reduce detection limits through signal amplification. Common immunoassay methods, such as colloidal gold immunochromatography, fluorescence immunochromatography, and chemiluminescence immunoassay, improve detection efficacy and sensitivity through specific antibody-antigen binding and nanotechnology. However, current rapid detection technologies of bitoxins in blood face challenges such as matrix interference and insufficient specificity, and they fall short in high-throughput detection of multiple toxins simultaneously. Future developments should focus on improving sample pretreatment, innovating signal amplification methods, enhancing specificity on recognition of elements, and designing portable detection devices and high-throughput platforms for simultaneous toxin analysis. These advancements aim to improve the sensitivity and reliability of detection methods, providing more accurate and convenient solutions for biotoxin detection in blood.

Objectives:To compare the HbA 1c results on capillary electrophoresis (CE), cation exchange-high performance liquid chromatography (CE-HPLC), and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Methods:902 normal samples without hemoglobin variants and 83 samples with hemoglobin variants were collected in 2020. The variants were divided into α-chain, β-chain, γ-chain, and δ-chain variants. The 902 samples without hemoglobin variants were measured by CE, CE-HPLC, and MALDI-TOF MS. Three methods were used for measuring α-chain, β-chain, and γ-chain compared with the liquid chromatography-tandem mass spectrometry (LC-MS/MS) reference method. According to the EP9-A3 guideline, Passing-Bablok regression and concordance correlation coefficient (CCC) were performed for correlation and consistency, respectively. The imprecision was assessed by coefficient of variance (CV). The mean relative bias was calculated and compared with the lowest biological variation bias of 2.3%.Results:All three methods met the acceptance of imprecision requirements (<2%). The R 2 and CCC for the normal samples were all above 0.95 between the pairwise comparison of CE, CE-HPLC, and MALDI-TOF MS. The mean relative bias between MALDI-TOF MS and CE-HPLC was higher than the lowest biological variation bias of 2.3%. The R 2 results between CE and LC-MS/MS results of α-chain, β-chain, γ-chain variants were>0.95, and the mean relative biases for γ-chain variants exceeded the lowest biological variation bias of 2.3%. A bad correlation ( R2=0.66) for β-chain variants was shown between CE-HPLC and LC-MS/MS and the mean relative biases of all variant samples exceeded 2.3%. MALDI-TOF MS showed good correlations with LC-MS/MS for three groups, and the mean relative biases for γ-chain variants were higher than 2.3%. Conclusion:MALDI-TOF MS and CE-HPLC with CE had good comparability in the measurement of HbA 1c in normal samples, butthe three methods showed interferences from different types of Hb variants and the CE method was affected with less interference.

Objective To explore the value of chromosomal microarray analysis(CMA)for the diagnosis of early spontaneous abortion,and to investigate the relationship between chromosomal abnormalities and early spontaneous abortion.Methods A total of 432 cases embryos were collected from June 2017 to December 2022 which occur early spontaneous abortion in Yangzhou Maternal and Child Health Hospital.We retrospectively analyze the results of chromosomal microarray analysis,and analyze the correlation between different gestational weeks and numerical chromosomal abnormalities and copy number variations.Results A total of 428 specimens were successfully analyzed by the CMA.Chromosomal abnormalities were identified in 270 specimens,including 212 cases of numerical chromosomal abnormalities,53 cases of copy number variations,and 5 cases of uniparental disomy.Most chromosomal abnormalities are trisomies,with 16-trisomy was the most common.Among the copy number variations,31 cases of pathogenic and likely pathogenic were detected,and 22 cases of clinically unknown copy number abnormalities were detected.There was no statistically significant difference in numerical chromosomal abnormalities among different gestational weeks(P>0.05),while the positive rate of copy number variations was highest at 10-11+6 weeks of pregnancy.Conclusion CMA can clarify the etiological diagnosis of early spontaneous abortion.It can not only detect chromosomal abnormalities,but also can detect copy number variations and even chromosome microdeletion syndrome,chromosome microduplication syndrome.In the study,numerical chromosomal abnormalities are the main cause of spontaneous abortion.

Objective:To study the relationship between hemoglobin glycation index (HGI) and blood lipid indices such as low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), and plasma atherogenic index (AIP).Methods:This cross-sectional study included 16 049 participants from the Beijing Apple Garden community between December 2011 and August 2012. The subjects were divided into three groups based on the HGI quartile: low ( n=5 388), medium ( n=5 249), and high ( n=5 412). The differences in blood lipid indicators between different HGI groups were compared and multivariate logistic regression model was established to analyze the association between HGI and dyslipidemia. And multivariate logistic regression model was established to analyze the relationship between HGI and blood lipid indicators in different glucose metabolism populations. Results:There were 16 049 participants in all (mean age: 56 years), including 10 452 women (65.1%). They were classified into normal glucose tolerance (9 093 cases), prediabetes (4 524 cases), and diabetes (2 432 cases) based on glucose tolerance status. In the general population, with the increase of HGI, LDL-C, non-HDL-C, and AIP gradually increased (all P values for trends were <0.05), and the proportion of abnormalities increased significantly ( χ2=101.40, 42.91, 39.80; all P<0.001). A multivariate logistic regression model was established, which suggested a significant correlation between HGI and LDL-C, non-HDL-C, and AIP (all P<0.05), after adjusting for factors such as age, sex, fasting blood glucose, hypertension, body mass index, smoking, and alcohol consumption. In the overall population, normal glucose tolerance group, and diabetes group, HGI had the highest correlation with non-HDL-C ( OR values of 1.325, 1.678, and 1.274, respectively); in the prediabetes group, HGI had a higher correlation with LDL-C ( OR value: 1.510); and in different glucose metabolism groups, AIP and HGI were both correlated ( OR: 1.208-1.250), but not superior to non-HDL-C and LDL-C. Conclusion:HGI was closely related to LDL-C, non HDL-C, and AIP in the entire population and people with different glucose metabolism, suggesting that HGI may be a predictor of atherosclerotic cardiovascular disease.

OBJECTIVE To prepare anemoside B4 （AB4） and programmed cell death ligand 1 （PDL1） siRNA （siP） co- delivered cRGD-modified targeting liposomes （AB4/siP-c-L）， and to study the cellular uptake in vitro. METHODS The cRGD- modified AB4-loaded targeted liposomes （AB4-c-L） were prepared by ethanol injection. AB4-c-L was mixed with 20 nmol/L siP in the same volume and AB4/siP-c-L was obtained through electrostatic adsorption. The particle size， Zeta potential， morphology， encapsulation efficiency and drug content， in vitro release behavior and serum stability of AB4/siP-c-L were investigated by laser scattering particle size tester， transmission electron microscopy， ultrafiltration centrifugation， dialysis and agar-gel electrophoresis block test. Cellular uptake of AB4/siP-c-L by Lewis lung cancer cells LLC and its intracellular localization were evaluated by flow cytometry and confocal laser scan technique. RESULTS The average particle size of AB4/siP-c-L was （187.4±3.1） nm， and the Zeta potential was （33.5±1.4） mV. AB4/siP-c-L was spheroidal in shape. The encapsulation efficiency and content of AB4 were （95.2±0.4） % and （1.0±0.2） mg/mL， respectively. AB4/siP-c-L could better package siP， and exhibited good serum stability， obvious pH sensitivity and sustained release property. The uptake rate of AB4/siP-c-L by LLC cells was significantly higher than that of free drug， and was able to accumulate in cytoplasm. CONCLUSIONS AB4/siP-c-L can effectively realize the co-loading of AB4 and gene drug siP， which has certain in vitro targeting to LLC cells.

In recent years, the perioperative surgical home model has been gradually applied to the posterior spinal fusion for adolescent idiopathic scoliosis. This review summarizes the application of perioperative surgical home model in adolescent idiopathic scoliosis surgery, including the concept, connotation and elements, hoping to provide reference and reference for complex and high-risk surgical procedures.

BACKGROUND: The hemoglobin glycation index (HGI) was developed to quantify glucose metabolism and individual differences and proved to be a robust measure of individual glycosylated hemoglobin (HbA1c) bias. Here, we aimed to explore the relationship between different HGIs and the risk of 5-year major adverse cardiovascular events (MACEs) by performing a large multicenter cohort study in China. METHODS: A total of 9791 subjects from the Risk Evaluation of Cancers in Chinese Diabetic Individuals: a Longitudinal Study (the REACTION study) were divided into five subgroups (Q1-Q5) with the HGI quantiles (≤5th, >5th and ≤33.3th, >33.3th and ≤66.7th, >66.7th and ≤95th, and >95th percentile). A multivariate logistic regression model constructed by the restricted cubic spline method was used to evaluate the relationship between the HGI and the 5-year MACE risk. Subgroup analysis between the HGI and covariates were explored to detect differences among the five subgroups. RESULTS: The total 5-year MACE rate in the nationwide cohort was 6.87% (673/9791). Restricted cubic spline analysis suggested a U-shaped correlation between the HGI values and MACE risk after adjustment for cardiovascular risk factors ( χ2 = 29.5, P <0.001). After adjustment for potential confounders, subjects with HGIs ≤-0.75 or >0.82 showed odds ratios (ORs) for MACE of 1.471 (95% confidence interval [CI], 1.027-2.069) and 2.222 (95% CI, 1.641-3.026) compared to subjects with HGIs of >-0.75 and ≤-0.20. In the subgroup with non-coronary heart disease, the risk of MACE was significantly higher in subjects with HGIs ≤-0.75 (OR, 1.540 [1.039-2.234]; P = 0.027) and >0.82 (OR, 2.022 [1.392-2.890]; P <0.001) compared to those with HGIs of ≤-0.75 or >0.82 after adjustment for potential confounders. CONCLUSIONS We found a U-shaped correlation between the HGI values and the risk of 5-year MACE. Both low and high HGIs were associated with an increased risk of MACE. Therefore, the HGI may predict the 5-year MACE risk.
Humans ; Cohort Studies ; Longitudinal Studies ; Diabetes Mellitus, Type 2/diagnosis* ; Maillard Reaction ; Glycated Hemoglobin ; Cardiovascular Diseases

Backgrounds::Inadequate sleep duration is associated with a higher risk of type 2 diabetes and the relationship is nonlinear. We aim to assess the curve relationship between night sleep duration and the incidence of type 2 diabetes in China.Methods::A cohort of 11,539 participants from the REACTION study without diabetes at baseline (2011) were followed until 2014 for the development of type 2 diabetes. The average number of hours of sleep per night was grouped. Incidence rates and odds ratios (ORs) were calculated for the development of diabetes in each sleep duration category.Results::Compared to people who sleep for 7 to 8 h/night, people with longer sleep duration (≥9 h/night) had a greater risk of type 2 diabetes (OR: 1.27; 95% CI: 1.01-1.61), while shorter sleep (<6 h/night) had no significant difference in risk of type 2 diabetes. When the dataset was stratified based on selected covariates, the association between type 2 diabetes and long sleep duration became more evident among individuals <65 years of age, male, body mass index <24 kg/m 2 or with hypertension or hyperlipidemia, no interaction effects were observed. Furthermore, compared to people persistently sleeping 7 to 9 h/night, those who persistently slept ≥9 h/night had a higher risk of type 2 diabetes. The optimal sleep duration was 6.3 to 7.5 h/night. Conclusions::Short or long sleep duration was associated with a higher risk of type 2 diabetes. Persistently long sleep duration increased the risk.