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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. Highlights: The levels of serum uric acid (UA) and creatinine in the first trimester of pregnant women were significantly lower than healthy non-pregnant women, probably because of the increase of glomerular filtration. Serum UA concentration in the first trimester was significantly higher in women with gestational diabetes mellitus (GDM) than in women with normal glucose tolerance (NGT). The association of serum UA in the first trimester and GDM were observed when serum UA was above 240 μmol/l, and the association was stronger in women aged over 35 years old and preBMI ≥ 24 kg/m2. To prevent GDM, healthy lifestyle intervention should be taken since early pregnancy to control serum UA concentration, especially in older and heavier pregnant women. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Our objective was to provide a method for selecting reference beam model and evaluating the dosimetric accuracy of volumetric modulated arc therapy (VMAT) plans delivered on three Elekta beam-matched linacs during radiation oncology. Beam data was measured on three beam-matched linacs including Synergy1, Synergy2 and VersaHD. For eighteen lung and esophagus cases, fifty-four plans were generated using VMAT technique with three linac beam models respectively for point dose measurement and three-dimensional dose measurement. Each VMAT plan was executed sequentially on three linacs respectively. Measurement results were compared with treatment planning system (TPS) calculation results for all VMAT plans. Among three beam-matched linacs, discrepancy in beam output factor, percentage depth dose at 5 cm, 10 cm, 20 cm depth and MLC leaf offset are all within 1% except 20 × 20 cm2 and 30 × 30 cm2 field sizes, and discrepancy in beam profile is all within 2%. With comparison between measurement result and TPS calculation result, the absolute dose deviations are within the range of ± 3%, and the gamma passing rates are all over 95% for all VMAT plans, which are within the tolerance of clinical acceptability. Compared with all plans delivered on Synegy1 and VersaHD, the point dose discrepancy between measured results and TPS calculated results for plans delivered on Synergy2 is smallest, and the gamma passing rate between measured results and TPS calculated results for plans delivered on Synergy2 is highest. The beam-matched linacs demonstrate good agreement between measurement result and TPS calculation result for VMAT plans. The method can be used for selecting reference beam model for VMAT plans. [ABSTRACT FROM AUTHOR]

G-protein-signaling modulator 1 (GPSM1) exhibits strong genetic association with Type 2 diabetes (T2D) and Body Mass Index in population studies. However, how GPSM1 carries out such control and in which types of cells are poorly understood. Here, we demonstrate that myeloid GPSM1 promotes metabolic inflammation to accelerate T2D and obesity development. Mice with myeloid-specific GPSM1 ablation are protected against high fat diet-induced insulin resistance, glucose dysregulation, and liver steatosis via repression of adipose tissue pro-inflammatory states. Mechanistically, GPSM1 deficiency mainly promotes TNFAIP3 transcription via the Gαi3/cAMP/PKA/CREB axis, thus inhibiting TLR4-induced NF-κB signaling in macrophages. In addition, we identify a small-molecule compound, AN-465/42243987, which suppresses the pro-inflammatory phenotype by inhibiting GPSM1 function, which could make it a candidate for metabolic therapy. Furthermore, GPSM1 expression is upregulated in visceral fat of individuals with obesity and is correlated with clinical metabolic traits. Overall, our findings identify macrophage GPSM1 as a link between metabolic inflammation and systemic homeostasis. G-protein-signaling modulator 1 (GPSM1), an accessory protein which activates heterotrimeric G-protein signaling, exhibits a genetic association with type 2 diabetes. Here the authors show that myeloid GPSM1 ablation in mice inhibits inflammation and metabolic dysfunction upon high fat diet. [ABSTRACT FROM AUTHOR]

Inter-fractional tumor variance would lead to insufficient dosage or overdose in tumor region during lung cancer radiotherapy. However, previous works have not considered influence of inter-fractional tumor amplitude variance at treatment position due to lack of effective evaluation method during radiotherapy, especially for lung tumor within the lower lobe. Our objective was to investigate inter-fractional tumor baseline shift and amplitude variance due to respiratory motion with 4DCBCT simulation and guidance during stereotactic ablative body radiotherapy (SABR) for lung tumor. Subject included 19 patients with lung tumor within the lower lobe. 4DCBCT-simulated images at treatment position were acquired sequentially to determine internal tumor volume (ITV) and reference tumor motion at simulation process. Compared with reference tumor motion, 95 4DCBCT-guided images were acquired during each treatment to evaluate inter-fractional tumor baseline shift and amplitude variance, which were − 0.0 ± 1.3 mm and − 0.2 ± 1.4 mm in left–right(LR) direction, 0.9 ± 2.3 mm and 0.4 ± 2.9 mm in superior-inferior (SI) direction, 0.1 ± 1.5 mm and − 0.4 ± 2.0 mm in anterior–posterior (AP) direction. ITV margin were 3.5 mm, 7.5 mm and 5.3 mm in LR, SI and AP directions with van Herk's (Int J Radiat Oncol Biol Phys 52(5):1407–1422, 2002) formula. 4DCBCT simulation and guidance is a reliable method to evaluate inter-fractional tumor variance during SABR for lung tumor within the lower lobe. ITV margin of 3.5 mm, 7.5 mm and 5.3 mm in LR, SI and AP directions would ensure greater tumor coverage during SABR for lung tumor within the lower lobe. [ABSTRACT FROM AUTHOR]

Ever since the social networks became the focus of a great number of researches, the privacy risks of published network data have also raised considerable concerns. To evaluate users' privacy risks, researchers have developed methods to de-anonymize the networks and identify the same person in the different networks. However, the existing solutions either require high-quality seed mappings for cold start, or exhibit low accuracy without fully exploiting the structural information, and entail high computation expense. In this paper, we propose a fast and effective seedless network de-anonymization approach simply relying on structural information, named RoleMatch. RoleMatch equips with a new pairwise node similarity measure and an efficient node matching algorithm. Through testing RoleMatch with both real and synthesized social networks, which are anonymized by several popular anonymization algorithms, we demonstrate that the RoleMatch receives superior performance compared with existing de-anonymization algorithms. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Reprogramming of pancreatic exocrine to insulin-producing cells by viral delivery of the genes encoding transcription factors neurogenin-3 ( Ngn3), pancreas/duodenum homeobox protein 1 ( Pdx1) and MafA is an efficient method for reversing diabetes in murine models. The variables that modulate reprogramming success are currently ill-defined. Methods: Here, we assess the impact of glycaemia on in vivo reprogramming in a mouse model of streptozotocin-induced beta cell ablation, using subsequent islet transplantation or insulin pellet implantation for creation of groups with differing levels of glycaemia before viral delivery of transcription factors. Results: We observed that hyperglycaemia significantly impaired reprogramming of exocrine to insulin-producing cells in their quantity, differentiation status and function. With hyperglycaemia, the reprogramming of acinar towards beta cells was less complete. Moreover, inflammatory tissue changes within the exocrine pancreas including macrophage accumulation were found, which may represent the tissue's response to clear the pancreas from insufficiently reprogrammed cells. Conclusions/interpretation: Our findings shed light on normoglycaemia as a prerequisite for optimal reprogramming success in a diabetes model, which might be important in other tissue engineering approaches and disease models, potentially facilitating their translational applications. [ABSTRACT FROM AUTHOR]

Direct lineage conversion is a promising approach to generate therapeutically important cell types for disease modeling and tissue repair. However, the survival and function of lineage-reprogrammed cells in vivo over the long term has not been examined. Here, using an improved method for in vivo conversion of adult mouse pancreatic acinar cells toward beta cells, we show that induced beta cells persist for up to 13 months (the length of the experiment), form pancreatic islet-like structures and support normoglycemia in diabetic mice. Detailed molecular analyses of induced beta cells over 7 months reveal that global DNA methylation changes occur within 10 d, whereas the transcriptional network evolves over 2 months to resemble that of endogenous beta cells and remains stable thereafter. Progressive gain of beta-cell function occurs over 7 months, as measured by glucose-regulated insulin release and suppression of hyperglycemia. These studies demonstrate that lineage-reprogrammed cells persist for >1 year and undergo epigenetic, transcriptional, anatomical and functional development toward a beta-cell phenotype. [ABSTRACT FROM AUTHOR]

To study the quality changes of blunt-snout bream ( Megalobrama amblycephala) stored at chilled temperature (0-9°C), a global stability index (GSI) method was developed. Sensory score, total aerobic counts (TAC), total volatile basic nitrogen (TVB-N), and K value (as a percentage of the ratio between HxR (hypoxanthine riboside)+Hx (hypoxanthine) to the total ATP (adenosine triphosphate) and its degradation products) were determined to form a GSI value, and a predictive model of GSI was established by combining zero order kinetics with the Arrhenius equation. The results showed that the goodness of fit remained a high level ( R>0.97), the activation energy (E) and the corresponding pre-exponential factor (k) were 83.49 kJ/mol and 4.78×10 respectively. Relative errors between experimental GSI values and predicted GSI values were all within ±15% before the 15 day. Therefore, the model could effectively predict the quality deterioration of blunt-snout bream during chilled storage. [ABSTRACT FROM AUTHOR]

Frequency dependent electric field measurements using in situ micro sensors, FDEMS, is a particularly useful technique for monitoring the changing state of a polymer in a composite (or in an adhesive joint or as a coating) during fabrication and aging during use in the field. Measurements can be made in the laboratory to monitor the polymerization process and to monitor durability and aging in an environmental chamber or other degradative environment. Equally important, the FDEMS in situ micro sensor monitoring technique can be used to monitor cure in production ovens and autoclaves on the plant floor as well as outside, for example, coatings on the surface of a ship in dry dock. Durability and aging can be monitored while the object is in use. Examples are a marine coating on a ship, the protective coating on the liner of an acid containing tank, a rocket propellant, an adhesive in a bond joint, or the polymer in a composite structure. [ABSTRACT FROM AUTHOR]

A correction to the article "Long-term persistence and development of induced pancreatic beta cells generated by lineage conversion of acinar cells" that was published in the November 17, 2014 issue is presented.