The Association of Hematological Parameters in Early and Middle Pregnancy with the Risk of Gestational Diabetes Mellitus.

Objective: Gestational diabetes mellitus (GDM) is a condition of glucose intolerance, which may be accompanied with inflammation. The levels of hematological parameters during pregnancy can reflect inflammatory conditions in pregnant women. This study aims to describe the dynamic change of blood cell parameters from the first trimester (6-12 weeks of gestation) to the second trimester (24-28 weeks of gestation) and to investigate the associations of these biomarkers with the risk of GDM. Methods: This study was a prospective double-center study conducted in Beijing, China (clinical trial number: NCT03246295). Hematological parameters were tested four times during the follow-up. Logistic regression analysis and Receiver Operating Characteristic (ROC) curve analysis were used to explore the association and predictive ability of hematological parameters for GDM. Results: There were 258 of 1027 pregnant women in our study developed GDM. Among the 1027 pregnant women, white blood cells (WBC) gradually increased, and red blood cells (RBC), hemoglobin (HGB), and platelet (PLT) tended to decrease from the first trimester to second trimester. After adjusting for confounding factors, higher levels of RBC, HGB, and PLT in both early and middle pregnancy were positively associated with GDM risk, whereas the level of WBC was associated with GDM risk only in early pregnancy. WBC, RBC, HGB, and PLT in early and middle pregnancy were all correlated with fasting insulin (FINS) in early pregnancy. Conclusion: Higher levels of hematological parameters in early and middle pregnancy were associated with glucose metabolism in early pregnancy and the subsequent risk of GDM.

Relationship between serum uric acid in early pregnancy and gestational diabetes mellitus: a prospective cohort study.

PURPOSE: The association between serum uric acid (UA) and gestational diabetes mellitus (GDM) was still unclear. Serum UA levels in pregnancy differed from that in non-pregnancy. This study aimed to investigate the changes of serum UA in early pregnancy, and to explore the association of serum UA with the risk of GDM. METHODS: A prospective double-center study including 873 singleton pregnant women was conducted in Beijing, China since 2019 (clinical trial number: NCT03246295). Seventy-eight healthy non-pregnant women were selected to compare the changes of biomarkers in pregnancy. Spearman correlation and logistic regression analysis were performed to measure the relationship between serum UA in early pregnancy and GDM. RESULTS: The incidence of GDM in our cohort was 20.27%(177/873). Compared with non-pregnant women, serum UA and creatinine decreased significantly during early pregnancy. Serum UA concentration in early pregnancy was significantly higher in GDM women than that in normal glucose tolerance (NGT) women [217.0(192.9, 272.0) µmol/l vs. 201.9(176.0, 232.0) µmol/l, p < 0.001]. After adjusted for confounding factors, elevated serum UA remained as an independent risk factor for GDM. The risk of GDM increased when serum UA was above 240 µmol/l (adjusted OR 1.964, 95% CI 1.296-2.977, p < 0.001), and stronger relationships between serum UA and GDM were observed in pregnant women aged over 35 years old and preBMI ≥ 24 kg/m2. CONCLUSION: The normal range of serum UA and creatinine in pregnant women were lower than those in non-pregnant women. It is essential to monitor serum UA concentrations since early pregnancy to alert and prevent GDM, especially in older and heavier pregnant women. CLINICAL TRIAL NUMBER: NCT03246295.

A Simplified Screening Model to Predict the Risk of Gestational Diabetes Mellitus in Pregnant Chinese Women.

INTRODUCTION: This study aimed to develop a simplified screening model to identify pregnant Chinese women at risk of gestational diabetes mellitus (GDM) in the first trimester. METHODS: This prospective study included 1289 pregnant women in their first trimester (6-12 weeks of gestation) with clinical parameters and laboratory data. Logistic regression was performed to extract coefficients and select predictors. The performance of the prediction model was assessed in terms of discrimination and calibration. Internal validation was performed through bootstrapping (1000 random samples). RESULTS: The prevalence of GDM in our study cohort was 21.1%. Maternal age, prepregnancy body mass index (BMI), a family history of diabetes, fasting blood glucose levels, the alanine transaminase to aspartate aminotransferase ratio (ALT/AST), and the triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) were selected for inclusion in the prediction model. The Hosmer-Lemeshow goodness-of-fit test showed good consistency between prediction and actual observation, and bootstrapping indicated good internal performance. The area under the receiver operating characteristic curve (ROC-AUC) of the multivariate logistic regression model and the simplified clinical screening model was 0.825 (95% confidence interval [CI] 0.797-0.853, P < 0.001) and 0.784 (95% CI 0.750-0.818, P < 0.001), respectively. The performance of our prediction model was superior to that of three other published models. CONCLUSION: We developed a simplified clinical screening model for predicting the risk of GDM in pregnant Chinese women. The model provides a feasible and convenient protocol to identify women at high risk of GDM in early pregnancy. Further validations are needed to evaluate the performance of the model in other populations. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03246295.

Mental representations mediate aversive learning in humans.

Mental representations of stimuli that are not physically present are critical for a range of cognitive capacities, including perception, memory, and learning. Overly robust mental representations, however, can contribute to hallucinations in healthy individuals and those diagnosed with psychotic illness. Measuring the strength of mental representations can thus provide insight into how the contents of the mind influence both adaptive and maladaptive behaviors. In rodents, the robustness of mental representations has been tested using the representation-mediated learning (RML) task, in which animals respond less to a cue after a stimulus that has previously been associated with this cue has been paired with illness. This suggests that the mental representation of the cue enters into a negative association during aversive learning, even though the cue is not physically present. Here, we developed a human version of the RML task in which participants initially learned associations between two visual symbols and two different appetitive food odors. Preference for the food odors was then tested immediately before and after a session in which one symbol was paired with an aversive noise. We observed that mediated learning, in the form of selective decrease in preference for the odor previously paired with the noise-predicting symbol, was directly proportional to direct aversive learning for the symbols themselves. These findings suggest that a mental representation of the odor entered into a negative association with the sound and pave the way for future studies aimed at characterizing the neural circuits of mediated learning in the human brain. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

ALT/AST as an Independent Risk Factor of Gestational Diabetes Mellitus Compared with TG/HDL-C.

OBJECTIVE: This study aimed to find the association between alanine transaminase-to-aspartate aminotransferase ratio (ALT/AST) and the incidence of gestational diabetes mellitus (GDM). METHODS: A total of 1128 pregnant women were included in this prospective, double-center, observational cohort study. ALT, AST and total bilirubin (TBil) were tested during 6-12 weeks of gestation and 75-g oral glucose tolerance test (OGTT) was conducted during 24-28 weeks of gestation to screen GDM. The association between ALT/AST and glucose concentration during OGTT was analyzed by linear regression model. The OR with 95% CI for incidence of GDM associated with ALT/AST was estimated by binary logistic regression. The discriminatory values of ALT/AST and triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) for GDM were calculated by the area under the receiver operating characteristic curve (ROC-AUC). RESULTS: The incidence of GDM was 22.07% (249/1128). ALT/AST was higher in GDM group than in NGT group (0.92 [0.75, 1.18] vs 0.80[0.65, 1.02], P <0.001). ALT/AST had positive correlations with fasting blood glucose, 1-hour and 2-hour blood glucose concentration during OGTT (0.089 [95% CI: 0.034, 0.163], 0.176 [95% CI: 0.052, 0.104], and 0.115 [95% CI: 0.199, 0.609], respectively). The OR of ALT/AST for incidence of GDM was 1.603 (95% CI:1.097, 2.344). The ROC-AUC of ALT/AST and TG/HDL-C reached 0.615 (95% CI: 0.575, 0.655) and 0.619 (95% CI: 0.580, 0.659), respectively. CONCLUSION: ALT/AST in early pregnancy was an independent risk factor of GDM. The predictive ability of ALT/AST was similar to TG/HDL-C for GDM.

HOMA-IR as a risk factor of gestational diabetes mellitus and a novel simple surrogate index in early pregnancy.

OBJECTIVE: To assess the association between insulin resistance and gestational diabetes mellitus (GDM) in early pregnancy and find a simple surrogate index of the homeostasis model assessment of insulin resistance (HOMA-IR). METHODS: A total of 700 pregnant women were included in this prospective, double-center, observational cohort study. The glucose and lipid metabolic characterization was performed at 6-12 weeks of pregnancy. All participants underwent a 75-g oral glucose tolerance test at 24-28 weeks of pregnancy. Linear regression analysis was applied to find a novel surrogate index of HOMA-IR. Binary logistic analysis was applied to estimate possible associations of different indices with GDM and insulin resistance. RESULTS: GDM was diagnosed in 145 of 700 women with singleton pregnancies (20.7%). HOMA-IR was higher in the GDM group than in the normal glucose tolerance (NGT) group and was an individual risk factor for GDM (adjusted risk ratio RR 1.371, 95% confidence interval [CI] 1.129-1.665, P < 0.001). TyHGB index as the surrogate index of HOMA-IR was represented as TG/HDL-C + 0.7*FBG (mmol/L) +0.1*preBMI (kg/m2 )(where TG/HDL-C is triglyceride/high-density lipoprotein cholesterol; FBG is fasting blood glucose, and preBMI is the pre-pregnancy body mass index [calculated as weight in kilograms divided by the square of height in meters]). The cut-off point of the TyHGB index was 6.0 (area under the curve 0.827, 95% CI 0.794-0.861, P < 0.001) for mild insulin resistance. CONCLUSION: Increased HOMA-IR in early pregnancy was a risk factor of GDM. TyHGB index could be a surrogate index of HOMA-IR and had a predictive value for GDM.

Predictability of HOMA-IR for Gestational Diabetes Mellitus in Early Pregnancy Based on Different First Trimester BMI Values.

Objective: To investigate the ability of homeostasis model assessment of insulin resistance (HOMA-IR) in early pregnancy for predicting gestational diabetes mellitus (GDM) in Chinese women with different first-trimester body mass index (FT-BMI) values. Methods: Baseline characteristics and laboratory tests were collected at the first prenatal visit (6−12 weeks of gestation). GDM was diagnosed by a 75 g oral glucose tolerance test (OGTT) at 24−28 weeks of gestation. Partial correlation analysis and binary logistic regression were applied to identify the association between HOMA-IR and GDM. The cutoff points for predicting GDM were estimated using receiver operating characteristic (ROC) curve analysis. Results: Of the total of 1343 women, 300 (22.34%) were diagnosed with GDM in the 24−28 weeks of gestation. Partial correlation analysis and binary logistic regression verified HOMA-IR as a significant risk factor for GDM in the normal weight subgroup (FT-BMI < 24 kg/m2) (adjusted OR 2.941 [95% CI 2.153, 4.016], P < 0.001), overweight subgroup (24.0 kg/m2 ≤ FT-BMI < 28.0 kg/m2) (adjusted OR 3.188 [95% CI 2.011, 5.055], P < 0.001), and obese subgroup (FT-BMI ≥ 28.0 kg/m2) (adjusted OR 9.415 [95% CI 1.712, 51.770], p = 0.01). The cutoff values of HOMA-IR were 1.52 (area under the curve (AUC) 0.733, 95% CI 0.701−0.765, p < 0.001) for all participants, 1.43 (AUC 0.691, 95% CI 0.651−0.730, p < 0.001) for normal weight women, 2.27 (AUC 0.760, 95% CI 0.703−0.818, p < 0.001) for overweight women, and 2.31 (AUC 0.801, 95% CI 0.696−0.907, p < 0.001) for obese women. Conclusions: Increased HOMA-IR in early pregnancy is a risk factor for GDM, and HOMA-IR can be affected by body weight. The cutoff value of HOMA-IR to predict GDM should be distinguished by different FT-BMI values.

The Predictive Ability of Hepatic Steatosis Index for Gestational Diabetes Mellitus and Large for Gestational Age Infant Compared with Other Noninvasive Indices Among Chinese Pregnancies: A Preliminary Double-center Cohort Study.

OBJECTIVE: To evaluate the association of hepatic steatosis index (HSI) in the first trimester and the risk of gestational diabetes mellitus (GDM) as well as large for gestational age (LGA) infant in Chinese women. METHODS: A total of 1082 pregnant women were included in this study. Maternal basic laboratory data, including ALT, AST, FBG, insulin, TG, and HDL-C, were tested during 6-12 weeks of gestation and anthropometric characteristics were monitored during gestation. A 75-g oral glucose tolerance test (OGTT) was conducted at 24-28 weeks of gestation. HSI, nonalcoholic fatty liver disease (NAFLD) liver fat score, triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) and triglyceride-glucose (TyG) index were calculated. Odds ratio with 95% confidence interval for subsequent risk of GDM and LGA by HSI quartiles were assessed by binary logistic regression model. The predictive ability of HSI for GDM and LGA was evaluated by the receiver operating characteristic (ROC) curve analysis and was compared with other indices. RESULTS: The incidence of GDM and LGA were 22.09% (239/1082) and 10.53% (87/826). HSI was higher in GDM group than in NGT group (median, interquartile range: 30.67, 27.20-35.10 vs 27.98, 25.70-30.82, P<0.001). Incidence of GDM was gradually increased with increasing HSI values. Women in the highest HSI quartile had significantly higher risk of LGA delivery than those in the lowest HSI quartile (P<0.05). The area under the ROC curves of HSI for GDM and LGA were higher than other indices, reaching 0.646 (95%CI: 0.605-0.686) and 0.600 (95%CI: 0.541-0.660), respectively. CONCLUSION: Higher HSI was independently associated with higher risk of GDM and LGA in Chinese women. HSI in the first trimester can predict the risk of GDM and LGA.

The prevalence of CGG repeat expansion mutation in FMR1 gene in the northern Chinese women of reproductive age.

BACKGROUND: The prevalence of CGG repeat expansion mutation in FMR1 gene varies among different populations. In this study, we investigated the prevalence of this mutation in women of reproductive age from northern China. METHODS: A total of 11,891 pre-conceptional or pregnant women, including 5037 pregnant women and 7357 women with the history of spontaneous abortion or induced abortion due to delayed growth of the embryos, were recruited. The number of CGG repeats in FMR1 was measured by the TRP-PCR method. We also offered genetic counseling and prenatal diagnosis to the women carrying pre-mutation or full mutation alleles. RESULTS: The prevalence of pre-mutation in reproductive women in northern China was 1/410, higher than that in southern China and Korea but lower than that in western countries. We also found that the prevalence of pre-mutation was relatively high (1/320) in women with abortion history. CONCLUSION: Screening for CGG repeat expansion mutation in FMR1 should be recommended to the women with the history of spontaneous abortion or induced abortion due to delayed growth of the embryos.

Rapid, in situ detection of cocaine residues based on paper spray ionization coupled with ion mobility spectrometry.

In this paper, a novel approach based on paper spray ionization coupled with ion mobility spectrometry (PSI-IMS) was developed for rapid, in situ detection of cocaine residues in liquid samples and on various surfaces (e.g. glass, marble, skin, wood, fingernails), without tedious sample pretreatment. The obvious advantages of PSI are its low cost, easy operation and simple configuration without using nebulizing gas or discharge gas. Compared with mass spectrometry, ion mobility spectrometry (IMS) takes advantage of its low cost, easy operation, and simple configuration without requiring a vacuum system. Therefore, IMS is a more congruous detection method for PSI in the case of rapid, in situ analysis. For the analysis of cocaine residues in liquid samples, dynamic responses from 5 µg mL(-1) to 200 µg mL(-1) with a linear coefficient (R(2)) of 0.992 were obtained. In this case, the limit of detection (LOD) was calculated to be 2 µg mL(-1) as signal to noise (S/N) was 3 with a relative standard deviation (RSD) of 6.5% for 11 measurements (n = 11). Cocaine residues on various surfaces such as metal, glass, marble, wood, skin, and fingernails were also directly analyzed before wiping the surfaces with a piece of paper. The LOD was calculated to be as low as 5 ng (S/N = 3, RSD = 6.3%, n = 11). This demonstrates the capability of the PSI-IMS method for direct detection of cocaine residues at scenes of cocaine administration. Our results show that PSI-IMS is a simple, sensitive, rapid and economical method for in situ detection of this illicit drug, which could help governments to combat drug abuse.

Fast quantitative detection of cocaine in beverages using nanoextractive electrospray ionization tandem mass spectrometry.

Without any sample pretreatment, effervescent beverage fluids were manually sprayed into the primary ion plume created by using a nanoelectrospray ionization source for direct ionization, and the analyte ions of interest were guided into an ion trap mass spectrometer for tandem mass analysis. Functional ingredients (e.g., vitamins, taurine, and caffeine, etc.) and spiked impurity (e.g., cocaine) in various beverages, such as Red Bull energy drink, Coco-cola, and Pepsi samples were rapidly identified within 1.5 s. The limit of detection was found to be 7-15 fg (S/N = 3) for cocaine in different samples using the characteristic fragment (m/z 150) observed in the MS(3) experiments. Typical relative standard deviation and recovery of this method were 6.9%-8.6% and 104%-108% for direct analysis of three actual samples, showing that nanoextractive electrospray ionization tandem mass spectrometry is a useful technique for fast screening cocaine presence in beverages.

Detection of melamine in milk products by surface desorption atmospheric pressure chemical ionization mass spectrometry.

Without any sample pretreatment, trace amounts of melamine in various milk products were rapidly detected noting the characteristic fragments (i.e., m/z 110, 85, and 60) in the MS/MS spectrum of protonated melamine molecules (m/z 127) recorded by using surface desorption atmospheric pressure chemical ionization mass spectrometry. Signal responses of the most abundant ionic fragment (m/z 85) of protonated melamine were well correlated with the amounts of melaime in milk products, showing a dynamic range about 5 orders of magnitude. The limit of detection (LOD) was found to be 3.4 x 10(-15) g/mm(2) (S/N = 3) for the detection of pure melamine deposited on the paper surface, which was much lower than that for detection of melamine in powdered milk (1.6 x 10(-11) g/mm(2), S/N = 3) or liquid milk (1.3 x 10(-12) g/mm(2), S/N = 3). The significant difference in LOD was ascribed to the relatively strong molecular interactions between melamine and the matrix such as proteins in the milk products. As demonstrated using desorption electrospray ionization (DESI) for melamine detection, weakening the molecular interaction between analytes and proteins is proposed as a general strategy to improve the sensitivity of ambient mass spectrometry for direct detection of analytes bound in protein matrixes. The relative standard deviation (RSD) and the recovery of this method were found to be 5.2 approximately 11.9% and 87 approximately 113%, respectively, for the detection of melamine in milk products. A single sample analysis was completed within a few seconds, providing a particularly convenient way to rapidly screen melamine presence in milk products.

Neutral desorption using a sealed enclosure to sample explosives on human skin for rapid detection by EESI-MS.

A novel air-tight neutral desorption enclosure has been fabricated to noninvasively sample low picograms of explosives 2,4,6-trinitrotoluene (TNT), hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), octahydro-1,3,5,7-tetranitro-1,3,5,7-tetraazocine (HMX), triacetone triperoxide (TATP), and nitroglycerin (NG) from human skin using a neutral nitrogen gas beam. Without further sample pretreatment, the explosive mixtures collected from the skin surface were directly transported by a nitrogen carrier gas over a 4-m distance for sensitive detection and rapid identification by extractive electrospray ionization tandem mass spectrometry.

Rapid differentiation of tea products by surface desorption atmospheric pressure chemical ionization mass spectrometry.

Protonated water molecules generated by an ambient corona discharge were directed to impact tea leaves for desorption/ionization at atmospheric pressure. Thus, a novel method based on surface desorption chemical ionization mass spectrometry (DAPCI-MS) has been developed for rapid analysis of tea products without any sample pretreatment. Under the optimized experimental conditions, DAPCI MS spectra of various tea samples are recorded rapidly, and the resulting mass spectra are chemical fingerprints that characterize the tea samples. On the basis of the mass spectral fingerprints, 40 tea samples including green tea, oolong tea, and jasmine tea were successfully differentiated by principal component analysis (PCA) of the mass spectral raw data. The PCA results were also validated with cluster analysis and supervised PCA analysis. The alteration of signal intensity caused by rough surfaces of tea leaves did not cause failure in the separation of the tea products. The experimental findings show that DAPCI-MS creates ions of both volatile and nonvolatile compounds in tea products at atmospheric pressure, providing a practical and convenient tool for high-throughput differentiation of tea products.

Surface desorption atmospheric pressure chemical ionization mass spectrometry for direct ambient sample analysis without toxic chemical contamination.

Ambient mass spectrometry, pioneered with desorption electrospray ionization (DESI) technique, is of increasing interest in recent years. In this study, a corona discharge ionization source is adapted for direct surface desorption chemical ionization of compounds on various surfaces at atmospheric pressure. Ambient air, with about 60% relative humidity, is used as a reagent to generate primary ions such as H(3)O(+), which is then directed to impact the sample surface for desorption and ionization. Under experimental conditions, protonated or deprotonated molecules of analytes present on various samples are observed using positive or negative corona discharge. Fast detection of trace amounts of analytes present in pharmaceutical preparations, viz foods, skins and clothes has been demonstrated without any sample pretreatment. Taking the advantage of the gasless setup, powder samples such as amino acids and mixtures of pharmaceutical preparations are rapidly analyzed. Impurities such as sudan dyes in tomato sauce are detected semiquantitatively. Molecular markers (e.g. putrescine) for meat spoilage are successfully identified from an artificially spoiled fish sample. Chemical warfare agent stimulants, explosives and herbicides are directly detected from the skin samples and clothing exposed to these compounds. This provides a detection limit of sub-pg (S/N > or = 3) range in MS2. Metabolites and consumed chemicals such as glucose are detected successfully from human skins. Conclusively, surface desorption atmospheric pressure chemical ionization (DAPCI) mass spectrometry, without toxic chemical contamination, detects various compounds in complex matrices, showing promising applications for analyses of human related samples.