Application of high resolution computed tomography image assisted classification model of middle ear diseases based on 3D-convolutional neural network. / 基于3Då·ç§¯ç¥žç»ç½‘ç»œçš„ä¸­è€³ç–¾ç— é«˜åˆ†è¾¨çŽ‡CTå›¾åƒè¾ åŠ©åˆ†ç±»è¯Šæ–­æ¨¡åž‹çš„åº”ç”¨.

OBJECTIVES: Chronic suppurative otitis media (CSOM) and middle ear cholesteatoma (MEC) are the 2 most common chronic middle ear diseases. In the process of diagnosis and treatment, the 2 diseases are prone to misdiagnosis and missed diagnosis due to their similar clinical manifestations. High resolution computed tomography (HRCT) can clearly display the fine anatomical structure of the temporal bone, accurately reflect the middle ear lesions and the extent of the lesions, and has advantages in the differential diagnosis of chronic middle ear diseases. This study aims to develop a deep learning model for automatic information extraction and classification diagnosis of chronic middle ear diseases based on temporal bone HRCT image data to improve the classification and diagnosis efficiency of chronic middle ear diseases in clinical practice and reduce the occurrence of missed diagnosis and misdiagnosis. METHODS: The clinical records and temporal bone HRCT imaging data for patients with chronic middle ear diseases hospitalized in the Department of Otorhinolaryngology, Xiangya Hospital from January 2018 to October 2020 were retrospectively collected. The patient's medical records were independently reviewed by 2 experienced otorhinolaryngologist and the final diagnosis was reached a consensus. A total of 499 patients (998 ears) were enrolled in this study. The 998 ears were divided into 3 groups: an MEC group (108 ears), a CSOM group (622 ears), and a normal group (268 ears). The Gaussian noise with different variances was used to amplify the samples of the dataset to offset the imbalance in the number of samples between groups. The sample size of the amplified experimental dataset was 1 806 ears. In the study, 75% (1 355) samples were randomly selected for training, 10% (180) samples for validation, and the remaining 15% (271) samples for testing and evaluating the model performance. The overall design for the model was a serial structure, and the deep learning model with 3 different functions was set up. The first model was the regional recommendation network algorithm, which searched the middle ear image from the whole HRCT image, and then cut and saved the image. The second model was image contrast convolutional neural network (CNN) based on twin network structure, which searched the images matching the key layers of HRCT images from the cut images, and constructed 3D data blocks. The third model was based on 3D-CNN operation, which was used for the final classification and diagnosis of the 3D data block construction, and gave the final prediction probability. RESULTS: The special level search network based on twin network structure showed an average AUC of 0.939 on 10 special levels. The overall accuracy of the classification network based on 3D-CNN was 96.5%, the overall recall rate was 96.4%, and the average AUC under the 3 classifications was 0.983. The recall rates of CSOM cases and MEC cases were 93.7% and 97.4%, respectively. In the subsequent comparison experiments, the average accuracy of some classical CNN was 79.3%, and the average recall rate was 87.6%. The precision rate and the recall rate of the deep learning network constructed in this study were about 17.2% and 8.8% higher than those of the common CNN. CONCLUSIONS: The deep learning network model proposed in this study can automatically extract 3D data blocks containing middle ear features from the HRCT image data of patients' temporal bone, which can reduce the overall size of the data while preserve the relationship between corresponding images, and further use 3D-CNN for classification and diagnosis of CSOM and MEC. The design of this model is well fitting to the continuous characteristics of HRCT data, and the experimental results show high precision and adaptability, which is better than the current common CNN methods.

[Study on effect of extract from Tibetan medicine Urtica hyperborean on anti-prostatic hyperplasia].

In this study,mouse models of benign prostatic hyperplasia induced by subcutaneous injection of testosterone propionate was used to investigate the therapeutic effect and mechanism of Urtica hyperborean( UW) extracts on prostate hyperplasia in mice. The effects of UW extracts on prostate index,serum epidermal growth factor( EGF) and dihydrotestosterone( DHT) in model mice were observed,and the EGF and anti-apoptotic factor( Bcl-2) mRNA expression levels were detected as well as pathological changes in prostate tissue. The results showed that the ethyl acetate extraction and alcohol soluble fraction of the UW could significantly reduce the prostate index,reduce the serum DHT and EGF levels( P<0. 01),and significantly decrease the EGF and Bcl-2 mRNA expression( P<0. 01),significantly improved the morphological structure of prostate tissue. The above results confirmed that ethyl acetate extract and alcohol-soluble parts of UW have a good preventive effect on mice prostatic hyperplasia model,and its mechanism may be to reduce androgen levels by regulating polypeptide growth factors and/or inhibiting cell hyperproliferation and promoting apoptosis. This study laid the foundation for the further research on UW.

[Rapid identification of constituents of Urtica hyperborea using UPLC-ESI-Q-TOF-MS/MS method].

This paper deals with the application of ultra-performance liquid chromatography tandem quadrupole time of flight mass spectrometry(UPLC-ESI-Q-TOF-MS/MS) method to rapidly determine and analyze the chemical constituents of methanol extract of Urtica hyperborea. We employed UPLC YMC-Triart C18(2. 1 mm×100 mm,1. 9 µm) column to UPLC analysis with acetonitrile-water(containing 0. 4% formic acid) in gradient as mobile phase. The flow rate was 0. 3 m L·min-1 gradient elution and column temperature was 30℃; the injection volume was 4 µL. ESI ion source was used to ensure the data collected in anegative ion mode. The chemical components of U. hyperborea were identified through retention time,exact relative molecular mass,cleavage fragments of MS/MS and reported data.The results indicated that a total of 31 compounds were identified,including 8 flavonoids,14 phenolic compounds,8 phenylpropanoids(4 coumarins and 4 lignans),and 1 steroidal compound,13 of which were confirmed by comparison. The UPLC-ESI-Q-TOF-MS/MS method could rapid identify the chemical components of U. hyperborea. The above compounds were discovered in U. hyperborea for the first time,which could provide theoretical foundation for further research on the basis of the pharmacodynamics of U. hyperborea.

Microarray Expression Profile of Circular RNAs in Peripheral Blood Mononuclear Cells from Active Tuberculosis Patients.

BACKGROUND/AIMS: Dysregulated expression of circular RNAs (circRNAs) was demonstrated to be implicated in many diseases. Here, we aimed to determine circRNA profile in peripheral blood mononuclear cells (PBMCs) from active tuberculosis (TB) patients to identify novel biomarkers for TB. METHODS: Expression profile of circRNAs in PBMCs from 3 active pulmonary TB patients and 3 healthy controls were analyzed by microarray assay. Six circRNAs were selected for validation using real time-quantitative PCR (qRT-PCR) in 40 TB patients and 40 control subjects. Receiver operating characteristic (ROC) curve was constructed to evaluate their values in TB diagnosis. Hsa_circRNA_001937 was chosen for further evaluation in an independent cohort consisting of 115 TB, 40 pneumonia, 40 COPD, 40 lung cancer patients and 90 control subjects. An eight-month follow up was performed in 20 newly diagnosed TB patients to investigate the expression change of hsa_circRNA_001937 after chemotherapy. RESULTS: We revealed and confirmed that a number of circRNAs were dysregulated in TB patients. Of the six studied physio circRNAs, the levels of hsa_circRNA_001937, hsa_circRNA_009024 and hsa_ circRNA_005086 were significantly elevated and hsa_circRNA_102101, hsa_circRNA_104964 and hsa_circRNA_104296 were significantly reduced in PBMCs from TB patients as compared to healthy controls. ROC curve analysis suggested that hsa_circRNA_001937 has the largest area under the curve (AUC = 0.873, P<0.001). Hsa_circRNA_001937 was significantly increased in patients with TB compared with patients with pneumonia, COPD and lung cancer. Hsa_ circRNA_001937 was correlated with TB severity (r = 0.4053, P = 0.010) and its expression significantly decreased after treatment. CONCLUSION: This study identified a set of deregulated circRNAs in active TB PBMCs, our data also suggest that hsa_circRNA_001937 can be used as a potential diagnostic biomarker of TB.

Engineering of regulated stochastic cell fate determination.

Both microbes and multicellular organisms actively regulate their cell fate determination to cope with changing environments or to ensure proper development. Here, we use synthetic biology approaches to engineer bistable gene networks to demonstrate that stochastic and permanent cell fate determination can be achieved through initializing gene regulatory networks (GRNs) at the boundary between dynamic attractors. We realize this experimentally by linking a synthetic GRN to a natural output of galactose metabolism regulation in yeast. Combining mathematical modeling and flow cytometry, we show that our engineered systems are bistable and that inherent gene expression stochasticity does not induce spontaneous state transitioning at steady state. Mathematical analysis predicts that stochastic cell fate determination in this case can only be realized when gene expression fluctuation occurs on or near attractor basin boundaries (the points of instability). Guided by numerical simulations, experiments are designed and performed with quantitatively diverse gene networks to test model predictions, which are verified by both flow cytometry and single-cell microscopy. By interfacing rationally designed synthetic GRNs with background gene regulation mechanisms, this work investigates intricate properties of networks that illuminate possible regulatory mechanisms for cell differentiation and development that can be initiated from points of instability.

Structure-constrained deep feature fusion for chronic otitis media and cholesteatoma identification.

Chronic suppurative otitis media (CSOM) and middle ear cholesteatoma (MEC) were two most common chronic middle ear disease(MED) clinically. Accurate differential diagnosis between these two diseases is of high clinical importance given the difference in etiologies, lesion manifestations and treatments. The high-resolution computed tomography (CT) scanning of the temporal bone presents a better view of auditory structures, which is currently regarded as the first-line diagnostic imaging modality in the case of MED. In this paper, we first used a region-of-interest (ROI) network to find the area of the middle ear in the entire temporal bone CT image and segment it to a size of 100*100 pixels. Then, we used a structure-constrained deep feature fusion algorithm to convert different characteristic features of the middle ear in three groups as suppurative otitis media (CSOM), middle ear cholesteatoma (MEC) and normal patches. To fuse structure information, we introduced a graph isomorphism network that implements a feature vector from neighbourhoods and the coordinate distance between vertices. Finally, we construct a classifier named the "otitis media, cholesteatoma and normal identification classifier" (OMCNIC). The experimental results achieved by the graph isomorphism network revealed a 96.36% accuracy in all CSOM and MEC classifications. The experimental results indicate that our structure-constrained deep feature fusion algorithm can quickly and effectively classify CSOM and MEC. It will help otologist in the selection of the most appropriate treatment, and the complications can also be reduced.

An analytical study of employee loyalty and corporate culture satisfaction assessment based on sentiment analysis.

As an important factor related to the interests of enterprises, the attitude and behavior of employees are related to the company's survival and the realization of business objectives. However, in recent years, with the rapid development of emerging industries and industry changes, the turnover rate of employees in the whole enterprise has been greatly improved. Frequent turnover of personnel will have a great impact on the stability of the company, the competitiveness of the enterprise, and the operating cost. Employee loyalty and corporate culture satisfaction assessment is the core of sustainable corporate development, but most of the traditional analysis studies are based on the performance approach, using employee overtime, employee achievement, and company effectiveness as data sources, the former performance data is only a side view of the company's situation, the latter as the data source of this study is a one-sided and involute form, and the data is not stable. Therefore, this paper proposes an analysis of employee loyalty and corporate culture satisfaction assessment based on sentiment analysis, using association rules and sentiment lexicons from anonymous employee evaluations to analyze the actual data.

Cx32 promotes autophagy and produces resistance to SN­induced apoptosis via activation of AMPK signalling in cervical cancer.

The roles of gap junctions (GJs) and its components, connexins, in the autophagy of cervical cancer cells have been rarely investigated. Our previous study demonstrated that connexin 32 (Cx32) exerted an anti­apoptotic effect on cervical cancer. However, as an important regulator of apoptosis, whether the autophagy is involved in the function of Cx32 on cervical cancer cells is not well defined. The present study aimed to investigate the role of Cx32 on autophagy and apoptosis inhibition in cervical cancer cells. The expression levels of Cx32 and the autophagy­associated protein LC3­â…¡ in paracancerous cervical tissues (n=30) and cervical cancer (n=50) tissues were determined via western blotting. In total, 45 cervical cancer specimens were used to evaluate the clinical relevance of Cx32 and LC3­â…¡. It was found that both Cx32 and LC3­â…¡ were upregulated in cervical cancer tissues compared with those in paracancerous cervical tissues. The effect of Cx32 on autophagy was examined by detecting the change of LC3­â…¡ using western blotting, transfection with enhanced green fluorescent protein­LC3 plasmid and transmission electron microscopy analysis. Overexpression of Cx32 significantly enhanced autophagy in HeLa­Cx32 cells, whereas knockdown of Cx32 suppressed autophagy in C­33A cells. The flow cytometry results demonstrated that Cx32 inhibited the apoptosis of cervical cancer cells by promoting autophagy. Moreover, Cx32 triggered autophagy via the activation of the AMP­activated protein kinase (AMPK) signalling, regardless of the presence or absence of GJs. Collectively, it was identified that Cx32 exerted its anti­apoptotic effect by activating autophagy via the AMPK pathway in cervical cancer, which demonstrates a novel mechanism for Cx32 in human cervical cancer progression.

6ß-Hy-droxy-eremophil-7(11)-en-8ß,12-olide.

The title eremophilenolide, C(15)H(22)O(3), is a natural compound isolated from Senecio laetus Edgew. The two cis-fused six-membered rings have chair confomations and the five-membered ring has a planar envelope conformation [maximum deviation = 0.010 (1) Å]. The ß-hy-droxy group participates in inter-molecular O-H⋯O hydrogen bonding, forming mol-ecular chains along the a axis.

Vlasoulides A and B, a pair of neuroprotective C32 dimeric sesquiterpenes with a hexacyclic 5/7/5/5/(5)/7 carbon skeleton from the roots of Vladimiria souliei.

Vlasoulides A and B (1 and 2), a pair of epimeric C32 sesquiterpene lactone dimers, featuring a 5/7/5/5/(5)/7 ring system were isolated from the roots of Vladimiria souliei. Their chemical structures were determined by comprehensive analysis of spectroscopic data, including HRESIMS and 1D and 2D NMR spectroscopic data. Their absolute configurations were established by Mosher's method and ECD experiments. Furthermore, biological studies showed that compound 1 showed prominent neuroprotective effects against glutamate-induced neurotoxicity in PC-12 cells, with EC50 values of 13.54 ± 0.33 µM, while, the EC50 value of compound 2 is greater than 30 µM.

[Comparison of mtDNA extraction from different parts of sarcosaphagous insects].

OBJECTIVE: To explore mitochondrial DNA (mtDNA) extraction effects of different parts from sarcosaphagous insects using improved cetyltriethylammnonium bromide (CTAB) method. METHODS: Thirteen Lucilia sericata (Meigen) and 13 Nicrophorus fossor (Erichson) were collected from the corpses of rabbits placed on the outdoor lawn in Huhehot district. Four parts (head, chest muscle, legs and wings) of insect were collected, and the mtDNA of all samples were extracted using CTAB method. The purity and concentration were tested using protein and nucleic acid spectrophotometry. The integrity of the extracted mtDNA and PCR products were checked by agarose gel electrophoresis. The PCR products were sequenced and the obtained sequences were imputed into GenBank for comparison. RESULTS: mtDNA were successfully extracted from 10 head samples, 6 legs samples, 4 wing samples and 13 chest muscle samples of the Lucilia sericata (Meigen). Also, mtDNA were successfully extracted from 5 head samples, 8 legs samples, 3 wing samples and 13 chest muscle samples of the Nicrophorus fossor (Erichson). CONCLUSION: mtDNA can be obtained from chest muscle and other parts of sarcosaphagous insects using the improved CTAB method.

Increasing insulin resistance predicts adverse pregnancy outcomes in women with gestational diabetes mellitus.

BACKGROUND: This study aimed to investigate the association between maternal insulin resistance (IR) in the late second trimester and pregnancy outcomes, as well as to identify risk factors of IR among women with gestational diabetes mellitus (GDM). METHODS: A retrospective study was conducted among 2647 women diagnosed with GDM. IR was evaluated using the homeostasis model assessment method for IR (HOMA-IR) in the late second trimester (between 24 and 28 weeks), and the lipid profiles were measured at the same time. Patients were divided into groups based on quartiles of HOMA-IR. The information on pregnancy outcomes and risk factors was extracted from the medical records of all participants and entered electronically. Logistic regression models were used to analyze the associations between HOMA-IR and pregnancy outcomes, as well as the associations between risk factors and HOMA-IR. RESULTS: Greater IR was associated with cesarean delivery, preterm delivery, macrosomia, and large for gestational age newborns, but only significantly associated with preterm delivery after adjustment for potential confounders (P < .001). Prepregnancy body mass index (BMI), weight gain before diagnosis of GDM, and triglycerides were significantly related with IR in the late second trimester (P < .001). Besides, the total area under the curve of the diagnostic 75-g oral glucose tolerance test and glycosylated hemoglobin A1c increased from the lowest to the highest HOMA-IR groups. CONCLUSIONS: Increasing IR in the late second trimester predicts adverse pregnancy outcomes especially for preterm delivery in women with GDM. Additionally, prepregnancy BMI and weight gain before diagnosis of GDM are independent risk factors for the development of IR.

Lineariifolianoids M-O, three rare sesquiterpene lactone dimers inhibiting NO production from Inula lineariifolia.

Three rare squiterpene lactone dimers lineariifolianoids M-O (1-3) were isolated from Inula lineariifolia for the first time. Their structures and absolute configuration were established on the basis of by NMR and MS spectroscopic data and X-ray crystallography. Furthermore, those three compounds exhibited significant inhibitory activity against LPS-induced NO production in RAW 264.7 macrophages with IC50 values of 1.421, 1.087 and 1.243 µM, respectively.

A new bilobalide isomer and two cis-coumaroylated flavonol glycosides from Ginkgo biloba leaves.

A new bilobalide isomer (1), together with two flavonol glycosides (2, 3), have been isolated and elucidated from the extract of Ginkgo biloba leaves. Significantly, 1 was a new sesquiterpene lactone with two lactone ring groups, both 2 and 3 were two flavonol glycosides with a same cis-coumaroylated fragment. Their chemical structures were elucidated by NMR and MS spectroscopic date and the absolute configuration of 1 was specific established by Cu-Kα X-ray crystallographic analyses. However, 1-3 showed no obvious anti-platelet aggregation activity.

Cyr61 overexpression induced by interleukin 8 via NF-kB signaling pathway and its role in tumorigenesis of gastric carcinoma in vitro.

Cyr61 (CCN1) is a multifunctional matricellular protein in bridging inflammation and cancer, involved in many biological functions such as tumorigenesis and carcinogenesis. The role of Cyr61 in gastric cancer (GC) has not been fully understood and needs to be investigated and clarified. We examined Cyr61 expression in 6 GC cell lines and stable transfection of recombinants in to BGC823 specifically down regulated the Cyr61 mRNA and protein expression shown by the analysis with western blot, RT-PCR, western blot and immunofluorescence assay. The cells treated with siRNA shown markedly reduced activity in growth, migration and invasion compared with parental BGC823 cells as well as mock transfectants. The Cyr61 deficient cells demonstrated significantly inhibited colony formation in soft agar and reduced tumorigenicity was showed in nude mice, NF-kB pathway evidently inactivated respectively. However, under the stimulation of IL-8, the siRNA-treated cells can restore the capacity of proliferation and invasion. IL-8 can induce the high expression of Cyr61 and MMP11 through NF-kB signal pathway. Silencing of Cyr61 can inhibit or minimize the proliferation and invasiveness of gastric cancer cell. The results imply that Cyr61 enhance the proliferation and invasion of gastric cancer cells and this process is partially modulated by the IL-8 up-regulation. Cyr61 may mediate the proliferation and development of gastric carcinoma.

Structural characterization and in vitro hypoglycemic activity of a glucan from Euryale ferox Salisb. seeds.

In this research, a polysaccharide fraction (EFSP-1) was obtained from the seeds of Euryale ferox Salisb. by DEAE sepharose FF and Superdex™ 75 gel chromatography. The average molecular weight (Mw) of EFSP-1 was 8.75 kDa. Monosaccharides composition analysis indicated that EFSP-1 was a glucan. The structure of EFSP-1 was characterized by analysis of FT-IR, GC-MS and NMR, which indicated that the backbone of EFSP-1 was mainly composed of (1→4)-α-D-Glcp with branches substituted at O-6 and terminated with T-α-D-Glcp. Moreover, the hypoglycemic effect of EFSP-1 was investigated by establishing insulin resistance HepG2 and 3T3-L1 cells. The results showed that EFSP-1 could increase glucose consumption by up-regulating the expression of GLUT-4 via activating PI3K/Akt signal pathway in IR cells. Hence, EFSP-1 could be a potential functional food to ameliorate insulin resistance for diabetes therapy.

Engineering of a synthetic quadrastable gene network to approach Waddington landscape and cell fate determination.

The process of cell fate determination has been depicted intuitively as cells travelling and resting on a rugged landscape, which has been probed by various theoretical studies. However, few studies have experimentally demonstrated how underlying gene regulatory networks shape the landscape and hence orchestrate cellular decision-making in the presence of both signal and noise. Here we tested different topologies and verified a synthetic gene circuit with mutual inhibition and auto-activations to be quadrastable, which enables direct study of quadruple cell fate determination on an engineered landscape. We show that cells indeed gravitate towards local minima and signal inductions dictate cell fates through modulating the shape of the multistable landscape. Experiments, guided by model predictions, reveal that sequential inductions generate distinct cell fates by changing landscape in sequence and hence navigating cells to different final states. This work provides a synthetic biology framework to approach cell fate determination and suggests a landscape-based explanation of fixed induction sequences for targeted differentiation.

High Prevalence of Gestational Diabetes Mellitus in Beijing: Effect of Maternal Birth Weight and Other Risk Factors.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with both short- and long-term adverse health consequences for both the mother and her offspring. The aim was to study the prevalence and risk factors for GDM in Beijing. METHODS: The study population consisted of 15,194 pregnant women attending prenatal care in 15 hospitals in Beijing, who delivered between June 20, 2013, and November 30, 2013, after 28 weeks of gestation. The participants were selected by cluster sampling from the 15 hospitals identified through random systematic sampling based on the number of deliveries in 2012. A questionnaire was designed to collect information. RESULTS: A total of 2987 (19.7%) women were diagnosed with GDM and 208 (1.4%) had diabetes in pregnancy (DIP). Age (OR: 1.053, 95% CI: 1.033-1.074, P < 0.01), family history of diabetes mellitus (OR: 1.481, 95% CI: 1.254-1.748, P < 0.01), prepregnancy body mass index (BMI) (OR: 1.481, 95% CI: 1.254-1.748, P < 0.01), BMI gain before 24 weeks (OR: 1.126, 95% CI: 1.075-1.800, P < 0.01), maternal birth weight (P < 0.01), and fasting plasma glucose at the first prenatal visit (P < 0.01) were identified as risk factors for GDM. In women with birth weight <3000 g, GDM rate was significantly higher. CONCLUSIONS: One out of every five pregnant women in Beijing either had GDM or DIP and this constitutes a huge health burden for health services. Prepregnancy BMI and weight gain before 24th week are important modifiable risk factors for GDM. Ensuring birth weight above 3000 g may help reduce risk for future GDM among female offsprings.

Relationship between Oral Glucose Tolerance Test Characteristics and Adverse Pregnancy Outcomes among Women with Gestational Diabetes Mellitus.

BACKGROUND: Hyperglycemia is associated with adverse pregnancy outcomes. However, the relationships between them remain ambiguous. This study aimed to analyze the effect of different oral glucose tolerance test (OGTT) results on adverse perinatal outcomes. METHODS: This retrospective cohort study included data from 15 hospitals in Beijing from June 20, 2013 to November 30, 2013. Women with gestational diabetes mellitus (GDM) were categorized according to the number and distribution of abnormal OGTT values, and the characteristics of adverse pregnancy outcomes were evaluated. Chi-square test and logistic regression analysis were used to determine the associations. RESULTS: In total, 14,741 pregnant women were included in the study population, 2927 (19.86%) of whom had GDM. As the number of hyperglycemic values in the OGTT increased, the risk of cesarean delivery, preterm births, large-for-gestational age (LGA), macrosomia, and neonatal complications significantly increased. Fasting hyperglycemia had clear associations with macrosomia (odds ratios [OR s]:1.84, 95% confidence intervals [CI s]: 1.39-2.42,P < 0.001), LGA (OR: 1.70, 95% CI: 1.29-2.25,P < 0.001), and cesarean delivery (OR: 1.33, 95% CI: 1.15-1.55,P < 0.001). The associations were stronger as fasting glucose increased. GDM diagnosed by hyperglycemia at OGTT-2 h was more likely to lead to preterm birth (OR: 1.50, 95% CI: 1.11-2.03,P < 0.01). CONCLUSIONS: Various characteristics of OGTTs are associated with different adverse outcomes. A careful reconsideration of GDM with hierarchical and individualized management according to OGTT characteristics is needed.

Data-based reconstruction of complex geospatial networks, nodal positioning and detection of hidden nodes.

Given a complex geospatial network with nodes distributed in a two-dimensional region of physical space, can the locations of the nodes be determined and their connection patterns be uncovered based solely on data? We consider the realistic situation where time series/signals can be collected from a single location. A key challenge is that the signals collected are necessarily time delayed, due to the varying physical distances from the nodes to the data collection centre. To meet this challenge, we develop a compressive-sensing-based approach enabling reconstruction of the full topology of the underlying geospatial network and more importantly, accurate estimate of the time delays. A standard triangularization algorithm can then be employed to find the physical locations of the nodes in the network. We further demonstrate successful detection of a hidden node (or a hidden source or threat), from which no signal can be obtained, through accurate detection of all its neighbouring nodes. As a geospatial network has the feature that a node tends to connect with geophysically nearby nodes, the localized region that contains the hidden node can be identified.