Augmentation of hepatocellular carcinoma malignancy by annexin A5 through modulation of invasion and angiogenesis.

BACKGROUND: Hepatocellular carcinoma (HCC) continues to play a substantial role in cancer-related morbidity and mortality, largely owing to its pronounced tumor heterogeneity and propensity for recurrence. This underscores the pressing need for in-depth examination of its highly malignant mechanisms. Annexin A5 (ANXA5), recognized as a hallmark tumor protein, has emerged as a focal point of interest because of its ambiguous function and mechanism in HCC prognosis. This study aimed to provide a comprehensive understanding of the role of ANXA5 in the malignant progression of human HCC cells by employing an integrative approach that combines conventional experimental methods with RNA sequencing. METHODS: Differences in ANXA5 expression between HCC tissues and corresponding nontumor tissues were evaluated using immunofluorescence (n = 25). Correlation analysis was subsequently performed to assess the association between ANXA5 expression and clinicopathological features (n = 65). The role of ANXA5 in human HCC cell lines with ANXA5 gene knockout and overexpression was explored in vitro using migration and invasion assays and Ki-67 indices and in vivo based on node mice xenograft model. A tube formation assay using human umbilical vein endothelial cells (HUVECs) was conducted to demonstrate the angiogenic effects of ANXA5 in HCC. Single-cell and bulk RNA sequencing was used to further investigate the underlying mechanisms involved. RESULTS: This study revealed that ANXA5 is highly expressed in patients with HCC and correlates with poor prognosis. Assays for migration, invasion, and proliferation based on ANXA5 gene knockout and overexpression systems in human HCC cell lines have demonstrated that ANXA5 enhances HCC malignancy in vitro and in vivo. Tube formation assays of HUVECs indicated that ANXA5 facilitates angiogenesis and recruits endothelial cells to HCC cells. Single-cell and bulk RNA sequencing data analysis further confirmed that ANXA5 expression in HCC is associated with hepatocyte metabolism, immune response activation, and various oncogenic signaling pathways. CONCLUSIONS: This study revealed a meaningful association between elevated ANXA5 expression in tumor tissues and an unfavorable prognosis in patients with HCC. In addition, ANXA5 promotes HCC malignancy by promoting invasion and angiogenesis. Thus, ANXA5 has emerged as a promising therapeutic target for HCC and has the potential to improve patient outcomes.

The Role of Phosphorus on Alkaline Hydrogen Oxidation Electrocatalysis for Ruthenium Phosphides.

Transition metal/p-block compounds are regarded as the most essential materials for electrochemical energy converting systems involving various electrocatalysis. Understanding the role of p-block element on the interaction of key intermediates and interfacial water molecule orientation at the polarized catalyst-electrolyte interface during the electrocatalysis is important for rational designing advanced p-block modified metal electrocatalysts. Herein, taking a sequence of ruthenium phosphides (including Ru2P, RuP and RuP2) as model catalysts, we establish a volcanic-relation between P-proportion and alkaline hydrogen oxidation reaction (HOR) activity. The dominant role of P for regulating hydroxyl binding energy is validated by active sites poisoning experiments, pH-dependent infection-point behavior, in situ surface enhanced infrared absorption spectroscopy, and density functional theory calculations, in which P could tailor the d-band structure of Ru, optimize the hydroxyl adsorption sites across the Ru-P moieties, thereby leading to improved proportion of strongly hydrogen-bonded water and facilitated proton-coupled electron transfer process, which are responsible for the enhanced alkaline HOR performance.

Enhanced anaerobic hydrogen production from cotton straws assisted by copper molybdate.

Hydrogen production from dark fermentation has potential application due to its environmental friendliness, low production cost, and sustainability. However, there is still an obstacle to improving the efficiency of bioH2 production to meet the requirements in practical applications. In this research, copper molybdates are synthesized under different pH conditions as additives to study their different influence processes during anaerobic hydrogen production from cotton straws with the pure cultural system. A series of results indicate that CuMoO4 with appropriate experimental conditions has the highest H2 yield at 191.3 mL/g straws at 37 °C, which is 236% higher than the control group. It can be shown that O. ethanolica 8KG-4 has an obvious accompanying with high stability and low cytotoxicity for this clean energy production system as well as the improvement of metabolic pathway. These results extend new thinking of obtaining higher H2 yield as a biofuel in future production.

Recent Progress in Silicon-Based Materials for Performance-Enhanced Lithium-Ion Batteries.

Silicon (Si) has been considered to be one of the most promising anode materials for high energy density lithium-ion batteries (LIBs) due to its high theoretical capacity, low discharge platform, abundant raw materials and environmental friendliness. However, the large volume changes, unstable solid electrolyte interphase (SEI) formation during cycling and intrinsic low conductivity of Si hinder its practical applications. Various modification strategies have been widely developed to enhance the lithium storage properties of Si-based anodes, including cycling stability and rate capabilities. In this review, recent modification methods to suppress structural collapse and electric conductivity are summarized in terms of structural design, oxide complexing and Si alloys, etc. Moreover, other performance enhancement factors, such as pre-lithiation, surface engineering and binders are briefly discussed. The mechanisms behind the performance enhancement of various Si-based composites characterized by in/ex situ techniques are also reviewed. Finally, we briefly highlight the existing challenges and future development prospects of Si-based anode materials.

Innovative Materials for Energy Storage and Conversion.

The metal chalcogenides (MCs) for sodium-ion batteries (SIBs) have gained increasing attention owing to their low cost and high theoretical capacity. However, the poor electrochemical stability and slow kinetic behaviors hinder its practical application as anodes for SIBs. Hence, various strategies have been used to solve the above problems, such as dimensions reduction, composition formation, doping functionalization, morphology control, coating encapsulation, electrolyte modification, etc. In this work, the recent progress of MCs as electrodes for SIBs has been comprehensively reviewed. Moreover, the summarization of metal chalcogenides contains the synthesis methods, modification strategies and corresponding basic reaction mechanisms of MCs with layered and non-layered structures. Finally, the challenges, potential solutions and future prospects of metal chalcogenides as SIBs anode materials are also proposed.

Enzyme Activity of Natural Products on Cytochrome P450.

Drug-metabolizing enzymes, particularly the cytochrome P450 (CYP450) monooxygenases, play a pivotal role in pharmacokinetics. CYP450 enzymes can be affected by various xenobiotic substrates, which will eventually be responsible for most metabolism-based herb-herb or herb-drug interactions, usually involving competition with another drug for the same enzyme binding site. Compounds from herbal or natural products are involved in many scenarios in the context of such interactions. These interactions are decisive both in drug discovery regarding the synergistic effects, and drug application regarding unwanted side effects. Herein, this review was conducted as a comprehensive compilation of the effects of herbal ingredients on CYP450 enzymes. Nearly 500 publications reporting botanicals' effects on CYP450s were collected and analyzed. The countries focusing on this topic were summarized, the identified herbal ingredients affecting enzyme activity of CYP450s, as well as methods identifying the inhibitory/inducing effects were reviewed. Inhibitory effects of botanicals on CYP450 enzymes may contribute to synergistic effects, such as herbal formulae/prescriptions, or lead to therapeutic failure, or even increase concentrations of conventional medicines causing serious adverse events. Conducting this review may help in metabolism-based drug combination discovery, and in the evaluation of the safety profile of natural products used therapeutically.

Identification of peripheral anterior synechia with anterior segment optical coherence tomography.

PURPOSE: To generate a model that evaluates the presence and extent of peripheral anterior synechia (PAS) based on anterior segment optical coherence tomography (AS-OCT). METHODS: The extent of PAS involvement in the eyes of patients with angle closure was assessed by indentation gonioscopy, and the part of non-PAS and PAS were assigned into two groups (NPAS and PAS). Anterior chamber angles were then imaged by AS-OCT with light-emitting diode (LED) irradiation directly into the pupils, leading to pupillary constriction and increasing anterior chamber angle width. Parameters including the angle opening distance at 750 µm anterior to the scleral spur (AOD750) and trabecular-iris space area at 750 µm anterior to the scleral spur (TISA750) were then obtained. The differences before and after LED irradiation of AOD750 and TISA750 were calculated and used to generate a PAS model based on binary logistic regression. Validation data were then tested. RESULTS: A total of 258 AS-OCT images in 14 eyes were assigned to the modeling data, and 120 were assigned to the validation data. There were no differences in AOD750 and TISA750 in the dark between NPAS and PAS (PAOD750 = 0.258, PTISA750 = 0.486), whereas after LED light exposure, TISA750light was larger in NPAS than in PAS (P = 0.047). The light-dark differences of both parameters showed significant differences between the two groups (PAOD750dif = 0.019, PTISA750dif < 0.001). The area under the curve of the model performance was 0.841, and the overall correct rate was 80.8% based on the validation data. CONCLUSIONS: The present study demonstrates that the AS-OCT-based PAS model could be useful in the identifying of the presence of synechial angle closure and evaluating the extent of PAS in a single eye.

Automated delineation of corneal layers on OCT images using a boundary-guided CNN.

Accurate segmentation of corneal layers depicted on optical coherence tomography (OCT) images is very helpful for quantitatively assessing and diagnosing corneal diseases (e.g., keratoconus and dry eye). In this study, we presented a novel boundary-guided convolutional neural network (CNN) architecture (BG-CNN) to simultaneously extract different corneal layers and delineate their boundaries. The developed BG-CNN architecture used three convolutional blocks to construct two network modules on the basis of the classical U-Net network. We trained and validated the network on a dataset consisting of 1,712 OCT images acquired on 121 subjects using a 10-fold cross-validation method. Our experiments showed an average dice similarity coefficient (DSC) of 0.9691, an intersection over union (IOU) of 0.9411, and a Hausdorff distance (HD) of 7.4423 pixels. Compared with several other classical networks, namely U-Net, Attention U-Net, Asymmetric U-Net, BiO-Net, CE-Net, CPFnte, M-Net, and Deeplabv3, on the same dataset, the developed network demonstrated a promising performance, suggesting its unique strength in segmenting corneal layers depicted on OCT images.

CHARACTERIZATION BY FRACTAL DIMENSION ANALYSIS OF THE RETINAL CAPILLARY NETWORK IN PARKINSON DISEASE.

PURPOSE: To characterize retinal capillary complexity by optical coherence tomography angiography in Parkinson disease. METHOD: Twenty-five Parkinson disease patients and 25 age- and gender-matched healthy controls were recruited. Optical coherence tomography angiography and optical coherence tomography imaged the superficial and deep retinal capillary plexuses and retinal structure. Retinal capillary skeleton density, retinal capillary perfusion density, and fractal dimension analysis of retinal capillary complexity were performed in the total annular zone and quadrant sectors. The thickness of retinal nerve fiber layer, ganglion cell layer and inner plexiform layer, and total retinal thickness were extracted from retinal structural images. Relationships among the retinal capillaries, retinal structure, and clinical parameters were analyzed. RESULTS: The superficial retinal capillary plexus in Parkinson disease patients had lower retinal capillary skeleton and perfusion densities and capillary complexity in the total annular zone and all quadrant sectors compared with healthy control subjects. The deep retinal capillary plexus retinal capillary complexity was decreased in the total annular zone and the superior and inferior quadrants. The retinal capillary complexity in the inferior quadrant was negatively correlated with the best-corrected visual acuity and disease duration (r = -0.61, r = -0.43, respectively, both P < 0.05). CONCLUSION: As determined by fractal analysis, retinal capillary complexity can be an objective biomarker in Parkinson disease.

Catalytic Activity Control via Crossover between Two Different Microstructures.

Metal nanocatalysts hold great promise for a wide range of heterogeneous catalytic reactions, while the optimization strategy of catalytic activity is largely restricted by particle size or shape control. Here, we demonstrate that a reversible microstructural control through the crossover between multiply twinned nanoparticle (MTP) and single crystal (SC) can be readily achieved by solvent post-treatment on gold nanoparticles (AuNPs). Polar solvents (e.g., water, methanol) direct the transformation from MTP to SC accompanied by the disappearance of twinning and stacking faults. A reverse transformation from SC to MTP is achieved in nonpolar solvent (e.g., toluene) mixed with thiol ligands. The transformation between two different microstructures is directly observed by in situ TEM and leads to a drastic modulation of catalytic activity toward the gas-phase selective oxidation of alcohols. On the basis of the combined experimental and theoretical investigations of alcohol chemisorption on these nanocatalysts, we propose that the exposure of {211}-like microfacets associated with twin boundaries and stack faults accounts for the strong chemisorption of alcohol molecules on MTP AuNPs and thus the exceptionally high catalytic activity.

Clustering of metabolic risk factors and adverse pregnancy outcomes: a prospective cohort study.

BACKGROUND: The relative contributions of a cluster of metabolic risk factors to pregnancy complications are not fully understood. We investigated the correlation between clustering of metabolic risk factors and adverse pregnancy outcomes. METHODS: This prospective cohort study was performed on pregnant women who sought health care during their whole gestation in a women's and children's hospital. The pregnancy outcomes were also followed. Pre-pregnancy overweight/obesity, as well as pregnancy high triglycerides, low high-density lipoprotein-cholesterol, hyperglycemia and raised blood pressure were defined as metabolic risk factors. Adverse pregnancy outcomes included preterm delivery, small/large for gestational age, preeclampsia, gestational diabetes mellitus, neonatal asphyxia and foetal demise. Stratified analyses were conducted on a total of 5535 women according to classification in each metabolic risk factor. The adjusted odds ratio (OR) for adverse pregnancy outcomes according to the number of clustering metabolic factors was calculated using the logistic regression analysis. RESULTS: The number of metabolic risk factors and adverse pregnancy outcomes were positively correlated (Ptrend < 0.001). Compared with women without a metabolic risk factor, women with one metabolic risk factor had a risk (OR = 1.67 95%CI 1.42-1.96) of adverse pregnancy outcomes. Women with a cluster of two metabolic risk factors tended to develop more adverse pregnancy outcomes (OR = 3.32 95% CI 2.69-4.10), and the risk was much higher in women with a cluster of three or more metabolic risk factors (OR = 10.40 95%CI 7.37-14.69). CONCLUSIONS: Pregnant women with a cluster of metabolic risk factors are more likely to have adverse pregnancy outcomes. Copyright © 2016 John Wiley & Sons, Ltd.

Lipoprotein-associated phospholipase A2 is associated with postpartum hypertension in women with history of preeclampsia.

Both hypertension and preeclampsia (PE) are considered as inflammatory diseases. Lipoprotein-associated phospholipase A2 (Lp-PLA2) is an inflammatory marker associated with lipid metabolism. We aimed to study the correlation and predictive value of Lp-PLA2 in postpartum hypertension after PE. A group of 160 PE patients (PE group) and a separate group of 160 normal pregnant women (control group) were recruited from January 2010 to October 2011. The average age in the PE group was 28.4 ± 4.5 years and the average gestational age was 34.7 ± 1.1 weeks. The average age in the control group was 27.8 ± 4.5 years and the average gestational age was 35.5 ± 1.2 weeks. General information (including age, gestational age, parity, history of metabolic disease, family history of high blood pressure, height, body weight before childbirth, and blood pressure) and blood samples were collected for measuring Lp-PLA2 and lipid parameters. From February to April in 2013, 153 cases in the PE group and 132 in the control group were re-called. We assessed their postpartum health, pregnancy, height, weight, and blood pressure. Serum mass of Lp-PLA2 in the PE group (210.67 ± 17.98 ng/mL) was significantly higher compared with that in the control group (174.72 ± 30.26 ng/mL) (P < 0.01). The pro-gestation BMI, systolic blood pressure (SBP), diastolic blood pressure, total cholesterol, triglyceride, and low-density lipoprotein-cholesterol (LDL-C) were also significantly higher. Correlation analysis showed that the level of Lp-PLA2 and SBP (r = 0.31), LDL-C (r = 0.37) were positively correlated. The incidence of postpartum hypertension in the PE group was higher than that in the normal control group. Logistic regression analysis showed that prenatal Lp-PLA2 mass was an independent risk factor for PE postpartum hypertension (OR 1.134,95 % CI 1.086-1.185). ROC curve analysis showed that the sensitivity of predicting postpartum hypertension was 73.2% and the specific degree was 86.6%, with Lp-PLA2 level of 217.75 ng/mL for boundary value. The onset of postpartum hypertension in PE patients may contribute to vascular inflammation, which is associated with antepartum lipid metabolism.

[Incident and related risk factors of hypertension in women with a history of preeclampsia].

OBJECTIVE: To investigate the prevalence of hypertension in women with a history of preeclampsia (PE) and to estimate related risk factors. METHODS: In this prospective case-control study, we collected clinical data from 809 women with a history of PE and 3 421 women with normal pregnancy from January 2008 to June 2012. Between November 2012 and April 2013, 651 women in PE group and 2 684 women with normal pregnancy group were recruited at the same time for collecting postpartum data including blood pressure, blood glucose and blood lipid. Binary logistic regression analysis was applied to analyze the relative factors of postpartum blood pressure. RESULTS: Prevalence of hypertension in PE group was higher than those with normal pregnancy (17.2% (112/651) vs. 1.1% (30/2 684), P < 0.01). Prevalence of hypertension in severe PE and mild PE patients was similar (20.1% (58/289) vs. 15.2% (55/362), P = 0.103). Binary logistic regression analysis indicated that progestational body mass index (OR = 1.379, 95% CI: 1.257-1.510, P < 0.05) , antepartum systolic blood pressure (OR = 1.025, 95%CI:1.012-1.040, P < 0.05) , antepartum triglyceride (OR = 1.002, 95% CI: 1.002-1.410, P < 0.05) , antepartum fasting blood glucose (OR = 1.733, 95% CI: 1.047-2.870, P < 0.05) , postpartum body mass index (OR = 1.279, 95% CI: 1.199-1.363, P < 0.05), postpartum fasting insulin (OR = 1.107, 95% CI: 1.055-1.162, P < 0.05) , systolic blood pressure difference between antepartum and postpartum (OR = 1.024, 95% CI :1.011-1.037, P < 0.05) , difference on triglyceride value between antepartum and postpartum (OR = 1.26, 95% CI: 1.069-1.486, P < 0.01), difference value of HOMA-IR between antepartum and postpartum (OR = 2.448, 95% CI: 1.330-4.500, P < 0.01) and difference value of high density lipoprotein cholesterol between antepartum and postpartum (OR = 1.699, 95% CI: 1.277-2.260, P < 0.05) were associated with hypertension after pregnancy. CONCLUSIONS: Women with history of PE are associated with higher risk of postpartum hypertension. Increased blood pressure, abnormal glucose and lipid metabolism during pregnancy are major risk factors for postpartum hypertension.

PCL/soy peptide nanofibers incorporated with riboflavin/HP-ß-CD assemblies for improving fruit storage quality.

In this study, we first successfully developed functionalized electrospun nanofibers (PCL/SP/ICs) loaded with Riboflavin (RF) for fruit preservation with inclusion complexes (RF/HP-ß-CD, IC) formed by encapsulating RF with hydroxypropyl-ß-cyclodextrin (HP-ß-CD) as a core material and soy peptide-assisted polycaprolactones (PCL/SP) as an overwrap material. Compared to 1 wt% and 5 wt% IC, nanofibers implanted with 3 wt% IC had an acceptable water contact angle (87.40°), good thermal stability, and superior mechanical properties. Also, RF/HP-ß-CD integration conferred antimicrobial and antioxidant capabilities to PCL/SP fiber membranes. High-performance liquid chromatography (HPLC) studies revealed that produced films of PCL/SP/ICs could continuously and controllably release RF (within 200 h), hence retarding grape degradation and decreasing mass loss rate and titratable acid content throughout an 8-day storage period. Based on these findings, electrospun nanofiber films may be useful for vitamin loading in active food packaging.

Study on microwave ablation temperature prediction model based on grayscale ultrasound texture and machine learning.

BACKGROUND: Temperature prediction is crucial in the clinical ablation treatment of liver cancer, as it can be used to estimate the coagulation zone of microwave ablation. METHODS: Experiments were conducted on 83 fresh ex vivo porcine liver tissues at two ablation powers of 15 W and 20 W. Ultrasound grayscale images and temperature data from multiple sampling points were collected. The machine learning method of random forests was used to train the selected texture features, obtaining temperature prediction models for sampling points and the entire ultrasound imaging area. The accuracy of the algorithm was assessed by measuring the area of the hyperechoic area in the porcine liver tissue cross-section and ultrasound grayscale images. RESULTS: The model exhibited a high degree of accuracy in temperature prediction and the identification of coagulation zone. Within the test sets for the 15 W and 20 W power groups, the average absolute error for temperature prediction was 1.14°C and 4.73°C, respectively. Notably, the model's accuracy in measuring the area of coagulation was higher than that of traditional ultrasonic grey-scale imaging, with error ratios of 0.402 and 0.182 for the respective power groups. Additionally, the model can filter out texture features with a high correlation to temperature, providing a certain degree of interpretability. CONCLUSION: The temperature prediction model proposed in this study can be applied to temperature monitoring and coagulation zone range assessment in microwave ablation.

A frogspawn inspired twin Mo2C/Ni composite with a conductive fibrous network as a robust bifunctional catalyst for advanced anion exchange membrane electrolyzers.

Anion exchange membrane water electrolysis (AEMWE) is considered one of the most cost-effective methods for producing green hydrogen. However, the performance of AEMWE is still restrained by the slow reaction kinetics and poor ion/electron transport of catalysts. Herein, inspired by frogspawn, Mo2C nanoparticles coupled with Ni were in situ embedded into a N-doped porous carbon nanofiber network (Mo2C/NCNTs@Ni) by chemical crosslinking electrospinning combined with carbonization. The unique bionic structure can guarantee favorable overall structural flexibility and fast ion/electron transport kinetics. As a result of the robust hydrogen binding energy of Mo2C, as well as the synergistic impact between Ni and Mo2C nanoparticles and the conductive network resembling frogspawn, the catalyst developed demonstrates excellent performance in both the HER and OER. When employed as a bifunctional catalyst in water electrolysis, Mo2C/NCNTs@Ni delivers overpotentials of 155 mV and 320 mV at 10 mA cm-2 for the HER and OER, respectively. In addition, the Mo2C/NCNTs@Ni also displays excellent long-term durability during a continuous operation test under different currents for 50 h. The assembled AEMWE electrolyzers with Mo2C/NCNTs@Ni as both the anode and cathode can achieve a current density of 82.5 mA cm-2 at 1.99 V, indicating great potential for industrial water splitting. These results give an insight for the development of advanced bifunctional electrocatalysts for the next generation of green and efficient H2 production by water electrolysis.

Dynamics of peripheral blood inflammatory index predict tumor pathological response and survival among patients with locally advanced non-small cell lung cancer who underwent neoadjuvant immunochemotherapy: a multi-cohort retrospective study.

Background: Static tumor features before initiating anti-tumor treatment were insufficient to distinguish responding from non-responding tumors under the selective pressure of immuno-therapy. Herein we investigated the longitudinal dynamics of peripheral blood inflammatory indexes (dPBI) and its value in predicting major pathological response (MPR) in non-small cell lung cancer (NSCLC). Methods: A total of 147 patients with NSCLC who underwent neoadjuvant immunochemotherapy were retrospectively reviewed as training cohort, and 26 NSCLC patients from a phase II trial were included as validation cohort. Peripheral blood inflammatory indexes were collected at baseline and as posttreatment status; their dynamics were calculated as their posttreatment values minus their baseline level. Least absolute shrinkage and selection operator algorithm was utilized to screen out predictors for MPR, and a MPR score was integrated. We constructed a model incorporating this MPR score and clinical predictors for predicting MPR and evaluated its predictive capacity via the area under the curve (AUC) of the receiver operating characteristic and calibration curves. Furthermore, we sought to interpret this MPR score in the context of micro-RNA transcriptomic analysis in plasma exosomes for 12 paired samples (baseline and posttreatment) obtained from the training cohort. Results: Longitudinal dynamics of monocyte-lymphocyte ratio, platelet-to-lymphocyte ratio, platelet-to-albumin ratio, and prognostic nutritional index were screened out as significant indicators for MPR and a MPR score was integrated, which was further identified as an independent predictor of MPR. Then, we constructed a predictive model incorporating MPR score, histology, and differentiated degree, which discriminated MPR and non-MPR patients well in both the training and validation cohorts with an AUC value of 0.803 and 0.817, respectively. Furthermore, micro-RNA transcriptomic analysis revealed the association between our MPR score and immune regulation pathways. A significantly better event-free survival was seen in subpopulations with a high MPR score. Conclusion: Our findings suggested that dPBI reflected responses to neoadjuvant immuno-chemotherapy for NSCLC. The MPR score, a non-invasive biomarker integrating their dynamics, captured the miRNA transcriptomic pattern in the tumor microenvironment and distinguished MPR from non-MPR for neoadjuvant immunochemotherapy, which could support the clinical decisions on the utilization of immune checkpoint inhibitor-based treatments in NSCLC patients.

[Evaluation of the diagnostic criteria of gestational metabolic syndrome and analysis of the risk factors].

OBJECTIVES: To investigate gestational multiple metabolic abnormalities aggregation and diagnostic criteria for gestational metabolic syndrome (GMS), and to analyze the risk factors of GMS. METHODS: A cohort study recruiting 309 pregnant women with preeclampsia, 627 pregnant women with gestational diabetes mellitus (GDM) and 1245 normal pregnant women was performed from January 2008 to December 2011 in Guangdong Women and Children's Hospital. Information regarding age, gestational weeks, basic blood pressure, admission blood pressure, height and body mass index(BMI)before pregnancy was recorded. Biochemical indicators including fasting plasma glucose (FPG), fasting insulin (FINS), total cholesterol (TC), triglyceride (TG), high density lipoprotein (HDL-C), low density lipoprotein (LDL-C), free fatty acids (FFA) were tested. GMS was diagnosed with three or all of the following conditions: (1) overweight and/or obesity before pregnancy (BMI ≥ 25 kg/m(2)); (2) hypertension with blood pressure ≥ 140/90 mm Hg (1 mm Hg = 0.133 kPa); (3) hyperglycemia:diagnosed as GDM; (4) dyslipidemia with TG ≥ 3.23 mmol/L. The incidence of GMS of the three groups were calculated and the risk factors were analyzed. RESULTS: (1) The age, gestational weeks, basic blood pressure, admission blood pressure, BMI before pregnancy of women with preeclampsia and women with GDM were significantly different compared to normal women, respectively (P < 0.01). (2) Biochemical indicators of women with preeclampsia were as following: FPG (4.6 ± 1.0) mmol/L, FINS (10.1 ± 5.6) mU/L, TC (6.3 ± 1.6) mmol/L, TG (3.9 ± 1.8) mmol/L, HDL-C (1.4 ± 0.4) mmol/L, LDL-C (3.0 ± 1.0) mmol/L, FFA (0.8 ± 0.4) mmol/L. And those in women with GDM were: FPG (4.7 ± 0.9) mmol/L, FINS (10.2 ± 5.8) mU/L, TC (5.7 ± 1.3) mmol/L, TG (3.2 ± 1.1) mmol/L, HDL-C (1.4 ± 0.4) mmol/L, LDL-C (2.7 ± 0.9) mmol/L, FFA (0.6 ± 0.3) mmol/L. In normal pregnant women they were: FPG (4.3 ± 0.5) mmol/L, FINS (9.0 ± 4.4) mU/L, TC (5.7 ± 1.1) mmol/L, TG (2.8 ± 1.1) mmol/L, HDL-C (1.5 ± 0.4) mmol/L, LDL-C (2.9 ± 0.8) mmol/L, FFA (0.6 ± 0.2) mmol/L. Statistic differences were found in preeclampsia and GDM women compared to normal women respectively (P < 0.01). (3) The prevalence of GMS in preeclampsia group and in GDM group was 26.2% (81/309) and 13.6% (85/627), statistically different from that of the control group (0)(P < 0.01). (4) Compared to normal women, women with preeclampsia had higher risk of developing GMS (OR = 1.62, 95%CI 1.31 - 2.00, P < 0.01). The risk factors were BMI (OR = 1.29, 95%CI 1.13 - 1.47) and TG (OR = 2.49, 95%CI 1.87 - 3.31). Also, women with GDM had higher risk of developing GMS than normal women (OR = 1.27, 95%CI 1.09 - 1.49, P < 0.01), and the risk factors were BMI (OR = 1.13, 95%CI 1.04 - 1.23) and TG (OR = 1.16, 95%CI 1.02 - 1.33). TG was the independent risk factor in both preeclampsia women and GDM women (P < 0.01, P < 0.05). HDL-C seemed to have less importance in identifying GMS (P > 0.05). CONCLUSIONS: According to the GMS diagnostic criteria used in this study, some preeclampsia patients and some GDM women had aggregation of multiple metabolic abnormalities including pre-pregnancy overweight/obesity, hyperglycemia, high blood pressure and dyslipidemia. TG was the independent risk factor for GMS. HDL-C seemed to have less importance in identifying GMS.

Effects of a heavy metal (cadmium) on the responses of subtropical coastal tree species to drought stress.

With global climate change and increased industrialization, drought and heavy metals have become common abiotic stress factors for coastal vegetation. In this study, we investigated the ecophysiological responses of the seedlings of three subtropical coastal tree species (Barringtonia racemosa, Hibiscus tiliaceus, and Terminalia neotaliala) to drought stress (D), cadmium addition (Cd), and their combined effects (Cd + D). The results showed that, for all three plant species, treatment D significantly decreased Amax, Y(II), qP, and ETR; increased the concentrations of PRO, soluble sugars, ABA, MDA, and O2-; and increased the activity of Rubisco. The concentrations of soluble sugars, MDA, and O2- were similar for treatments D and Cd; the only difference was that qP, Amax, and ETR values of B. racemosa and the Amax value of H. tiliaceus were significantly lower in treatment Cd than in control. The concentrations of PRO, soluble sugars, ABA, and MDA were significantly lower for treatment Cd + D than for treatment D. The O2- concentration was positively correlated with the concentrations of soluble sugars and PRO, indicating that osmoregulation was important for the responses of the plants to oxidative stress. ABA was positively correlated with MDA, indicating that ABA was involved in the response to oxidative stress. These results, which show that Cd may weaken the physiological responses of coastal plants to drought stress by increasing ABA accumulation, may provide guidance for coastal ecosystem management in South China.

CMS-NET: deep learning algorithm to segment and quantify the ciliary muscle in swept-source optical coherence tomography images.

Background: The ciliary muscle plays a role in changing the shape of the crystalline lens to maintain the clear retinal image during near work. Studying the dynamic changes of the ciliary muscle during accommodation is necessary for understanding the mechanism of presbyopia. Optical coherence tomography (OCT) has been frequently used to image the ciliary muscle and its changes during accommodation in vivo. However, the segmentation process is cumbersome and time-consuming due to the large image data sets and the impact of low imaging quality. Objectives: This study aimed to establish a fully automatic method for segmenting and quantifying the ciliary muscle on the basis of optical coherence tomography (OCT) images. Design: A perspective cross-sectional study. Methods: In this study, 3500 signed images were used to develop a deep learning system. A novel deep learning algorithm was created from the widely used U-net and a full-resolution residual network to realize automatic segmentation and quantification of the ciliary muscle. Finally, the algorithm-predicted results and manual annotation were compared. Results: For segmentation performed by the system, the total mean pixel value difference (PVD) was 1.12, and the Dice coefficient, intersection over union (IoU), and sensitivity values were 93.8%, 88.7%, and 93.9%, respectively. The performance of the system was comparable with that of experienced specialists. The system could also successfully segment ciliary muscle images and quantify ciliary muscle thickness changes during accommodation. Conclusion: We developed an automatic segmentation framework for the ciliary muscle that can be used to analyze the morphological parameters of the ciliary muscle and its dynamic changes during accommodation.