Prenatal Diagnosis of Placenta Accreta Spectrum Disorders: Deep Learning Radiomics of Pelvic MRI.

BACKGROUND: Diagnostic performance of placenta accreta spectrum (PAS) by prenatal MRI is unsatisfactory. Deep learning radiomics (DLR) has the potential to quantify the MRI features of PAS. PURPOSE: To explore whether DLR from MRI can be used to identify pregnancies with PAS. STUDY TYPE: Retrospective. POPULATION: 324 pregnant women (mean age, 33.3 years) suspected PAS (170 training and 72 validation from institution 1, 82 external validation from institution 2) with clinicopathologically proved PAS (206 PAS, 118 non-PAS). FIELD STRENGTH/SEQUENCE: 3-T, turbo spin-echo T2-weighted images. ASSESSMENT: The DLR features were extracted using the MedicalNet. An MRI-based DLR model incorporating DLR signature, clinical model (different clinical characteristics between PAS and non-PAS groups), and MRI morphologic model (radiologists' binary assessment for the PAS diagnosis) was developed. These models were constructed in the training dataset and then validated in the validation datasets. STATISTICAL TESTS: The Student t-test or Mann-Whitney U, χ2 or Fisher exact test, Kappa, dice similarity coefficient, intraclass correlation coefficients, least absolute shrinkage and selection operator logistic regression, multivariate logistic regression, receiver operating characteristic (ROC) curve, DeLong test, net reclassification improvement (NRI) and integrated discrimination improvement (IDI), calibration curve with Hosmer-Lemeshow test, decision curve analysis (DCA). P < 0.05 indicated a significant difference. RESULTS: The MRI-based DLR model had a higher area under the curve than the clinical model in three datasets (0.880 vs. 0.741, 0.861 vs. 0.772, 0.852 vs. 0.675, respectively) or MRI morphologic model in training and independent validation datasets (0.880 vs. 0.760, 0.861, vs. 0.781, respectively). The NRI and IDI were 0.123 and 0.104, respectively. The Hosmer-Lemeshow test had nonsignificant statistics (P = 0.296 to 0.590). The DCA offered a net benefit at any threshold probability. DATA CONCLUSION: An MRI-based DLR model may show better performance in diagnosing PAS than a clinical or MRI morphologic model. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

How mobility pattern shapes the association between static green space and dynamic green space exposure.

Greenspaces are crucial for enhancing mental and physical health. Recent research has shifted from static methods of assessing exposure to greenspaces, based on fixed locations, to dynamic approaches that account for individual mobility. These dynamic evaluations utilize advanced technologies like GPS tracking and remote sensing to provide more precise exposure estimates. However, little work has been conducted to compare dynamic and static exposure assessments and the effect of individual mobility on these evaluations. This study delves into how greenspaces around homes and workplaces, along with mobility patterns, affect dynamic greenspace exposure in Hong Kong. Data was collected from 787 participants in four communities in Hong Kong using GPS, portable sensors, and surveys. Using multiple statistical tests, our study revealed significant variations in participants' daily mobility patterns across socio-demographic and temporal factors. Further, using linear mixed-effects models, we identified complex and statistically significant interactions between participants' static greenspace exposure and their mobility patterns. Our findings suggest that individual mobility patterns significantly modify the relationship between static and dynamic greenspace exposure and play a critical role in explaining socio-demographic and temporal context differences in the relationship between static and dynamic greenspace exposure.

High-quality chromosome-level de novo assembly of the Trifolium repens.

BACKGROUND: White clover (Trifolium repens L.), an excellent perennial legume forage, is an allotetraploid native to southeastern Europe and southern Asia. It has high nutritional, ecological, genetic breeding, and medicinal values and exhibits excellent resistance to cold, drought, trample, and weed infestation. Thus, white clover is widely planted in Europe, America, and China; however, the lack of reference genome limits its breeding and cultivation. This study generated a white clover de novo genome assembly at the chromosomal level and annotated its components. RESULTS: The PacBio third-generation Hi-Fi assembly and sequencing methods generated a 1096 Mb genome size of T. repens, with contigs of N50 = 14 Mb, scaffolds of N50 = 65 Mb, and BUSCO value of 98.5%. The newly assembled genome has better continuity and integrity than the previously reported white clover reference genome; thus provides important resources for the molecular breeding and evolution of white clover and other forage. Additionally, we annotated 90,128 high-confidence gene models from the genome. White clover was closely related to Trifolium pratense and Trifolium medium but distantly related to Glycine max, Vigna radiata, Medicago truncatula, and Cicer arietinum. The expansion, contraction, and GO functional enrichment analysis of the gene families showed that T. repens gene families were associated with biological processes, molecular function, cellular components, and environmental resistance, which explained its excellent agronomic traits. CONCLUSIONS: This study reports a high-quality de novo assembly of white clover genome obtained at the chromosomal level using PacBio Hi-Fi sequencing, a third-generation sequencing. The generated high-quality genome assembly of white clover provides a key basis for accelerating the research and molecular breeding of this important forage crop. The genome is also valuable for future studies on legume forage biology, evolution, and genome-wide mapping of quantitative trait loci associated with the relevant agronomic traits.

People's political views, perceived social norms, and individualism shape their privacy concerns for and acceptance of pandemic control measures that use individual-level georeferenced data.

BACKGROUND: As the COVID-19 pandemic became a major global health crisis, many COVID-19 control measures that use individual-level georeferenced data (e.g., the locations of people's residences and activities) have been used in different countries around the world. Because these measures involve some disclosure risk and have the potential for privacy violations, people's concerns for geoprivacy (locational privacy) have recently heightened as a result, leading to an urgent need to understand and address the geoprivacy issues associated with COVID-19 control measures that use data on people's private locations. METHODS: We conducted an international cross-sectional survey in six study areas (n = 4260) to examine how people's political views, perceived social norms, and individualism shape their privacy concerns, perceived social benefits, and acceptance of ten COVID-19 control measures that use individual-level georeferenced data. Multilevel linear regression models were used to examine these effects. We also applied multilevel structure equation models (SEMs) to explore the direct, indirect, and mediating effects among the variables. RESULTS: We observed a tradeoff relationship between people's privacy concerns and the acceptance (and perceived social benefits) of the control measures. People's perceived social tightness and vertical individualism are positively associated with their acceptance and perceived social benefits of the control measures, while horizontal individualism has a negative association. Further, people with conservative political views and high levels of individualism (both vertical and horizontal) have high levels of privacy concerns. CONCLUSIONS: Our results first suggest that people's privacy concerns significantly affect their perceived social benefits and acceptance of the COVID-19 control measures. Besides, our results also imply that strengthening social norms may increase people's acceptance and perceived social benefits of the control measures but may not reduce people's privacy concerns, which could be an obstacle to the implementation of similar control measures during future pandemics. Lastly, people's privacy concerns tend to increase with their conservatism and individualism.

Self-Attention Mechanism-Based Head Pose Estimation Network with Fusion of Point Cloud and Image Features.

Head pose estimation serves various applications, such as gaze estimation, fatigue-driven detection, and virtual reality. Nonetheless, achieving precise and efficient predictions remains challenging owing to the reliance on singular data sources. Therefore, this study introduces a technique involving multimodal feature fusion to elevate head pose estimation accuracy. The proposed method amalgamates data derived from diverse sources, including RGB and depth images, to construct a comprehensive three-dimensional representation of the head, commonly referred to as a point cloud. The noteworthy innovations of this method encompass a residual multilayer perceptron structure within PointNet, designed to tackle gradient-related challenges, along with spatial self-attention mechanisms aimed at noise reduction. The enhanced PointNet and ResNet networks are utilized to extract features from both point clouds and images. These extracted features undergo fusion. Furthermore, the incorporation of a scoring module strengthens robustness, particularly in scenarios involving facial occlusion. This is achieved by preserving features from the highest-scoring point cloud. Additionally, a prediction module is employed, combining classification and regression methodologies to accurately estimate head poses. The proposed method improves the accuracy and robustness of head pose estimation, especially in cases involving facial obstructions. These advancements are substantiated by experiments conducted using the BIWI dataset, demonstrating the superiority of this method over existing techniques.

Gate-Tunable Transport in Quasi-One-Dimensional α-Bi4I4 Field Effect Transistors.

Bi4I4 belongs to a novel family of quasi-one-dimensional (1D) topological insulators (TIs). While its ß phase was demonstrated to be a prototypical weak TI, the α phase, long thought to be a trivial insulator, was recently predicted to be a rare higher order TI. Here, we report the first gate tunable transport together with evidence for unconventional band topology in exfoliated α-Bi4I4 field effect transistors. We observe a Dirac-like longitudinal resistance peak and a sign change in the Hall resistance; their temperature dependences suggest competing transport mechanisms: a hole-doped insulating bulk and one or more gate-tunable ambipolar boundary channels. Our combined transport, photoemission, and theoretical results indicate that the gate-tunable channels likely arise from novel gapped side surface states, two-dimensional (2D) TI in the bottommost layer, and/or helical hinge states of the upper layers. Markedly, a gate-tunable supercurrent is observed in an α-Bi4I4 Josephson junction, underscoring the potential of these boundary channels to mediate topological superconductivity.

Associations between COVID-19 risk, multiple environmental exposures, and housing conditions: A study using individual-level GPS-based real-time sensing data.

Few studies have used individual-level data to explore the association between COVID-19 risk with multiple environmental exposures and housing conditions. Using individual-level data collected with GPS-tracking smartphones, mobile air-pollutant and noise sensors, an activity-travel diary, and a questionnaire from two typical neighborhoods in a dense and well-developed city (i.e., Hong Kong), this study seeks to examine 1) the associations between multiple environmental exposures (i.e., different types of greenspace, PM2.5, and noise) and housing conditions (i.e., housing types, ownership, and overcrowding) with individuals' COVID-19 risk both in residential neighborhoods and along daily mobility trajectories; 2) which social groups are disadvantaged in COVID-19 risk through the perspective of the neighborhood effect averaging problem (NEAP). Using separate multiple linear regression and logistical regression models, we found a significant negative association between COVID-19 risk with greenspace (i.e., NDVI) both in residential areas and along people's daily mobility trajectories. Meanwhile, we also found that high open space and recreational land exposure and poor housing conditions were positively associated with COVID-19 risk in high-risk neighborhoods, and noise exposure was positively associated with COVID-19 risk in low-risk neighborhoods. Further, people with work places in high-risk areas and poor housing conditions were disadvantaged in COVID-19 risk.

A de novo assembled high-quality chromosome-scale Trifolium pratense genome and fine-scale phylogenetic analysis.

BACKGROUND: Red clover (Trifolium pratense L.) is a diploid perennial temperate legume with 14 chromosomes (2n = 14) native to Europe and West Asia, with high nutritional and economic value. It is a very important forage grass and is widely grown in marine climates, such as the United States and Sweden. Genetic research and molecular breeding are limited by the lack of high-quality reference genomes. In this study, we used Illumina, PacBio HiFi, and Hi-C to obtain a high-quality chromosome-scale red clover genome and used genome annotation results to analyze evolutionary relationships among related species. RESULTS: The red clover genome obtained by PacBio HiFi assembly sequencing was 423 M. The assembly quality was the highest among legume genome assemblies published to date. The contig N50 was 13 Mb, scaffold N50 was 55 Mb, and BUSCO completeness was 97.9%, accounting for 92.8% of the predicted genome. Genome annotation revealed 44,588 gene models with high confidence and 52.81% repetitive elements in red clover genome. Based on a comparison of genome annotation results, red clover was closely related to Trifolium medium and distantly related to Glycine max, Vigna radiata, Medicago truncatula, and Cicer arietinum among legumes. Analyses of gene family expansions and contractions and forward gene selection revealed gene families and genes related to environmental stress resistance and energy metabolism. CONCLUSIONS: We report a high-quality de novo genome assembly for the red clover at the chromosome level, with a substantial improvement in assembly quality over those of previously published red clover genomes. These annotated gene models can provide an important resource for molecular genetic breeding and legume evolution studies. Furthermore, we analyzed the evolutionary relationships among red clover and closely related species, providing a basis for evolutionary studies of clover leaf and legumes, genomics analyses of forage grass, the improvement of agronomic traits.

MRI-radiomics-clinical-based nomogram for prenatal prediction of the placenta accreta spectrum disorders.

OBJECTIVES: To investigate whether an MRI-radiomics-clinical-based nomogram can be used to prenatal predict the placenta accreta spectrum (PAS) disorders. METHODS: The pelvic MR images and clinical data of 156 pregnant women with pathologic-proved PAS (PAS group) and 115 pregnant women with no PAS (non-PAS group) identified by clinical and prenatal ultrasonic examination were retrospectively collected from two centers. These pregnancies were divided into a training (n = 133), an independent validation (n = 57), and an external validation (n = 81) cohort. Radiomic features were extracted from images of transverse oblique T2-weighted imaging. A radiomics signature was constructed. A nomogram, composed of MRI morphological findings, radiomic features, and prenatal clinical characteristics, was developed. The discrimination and calibration of the nomogram were conducted to assess its performance. RESULTS: A radiomics signature, including three PAS-related features, was associated with the presence of PAS in the three cohorts (p < 0.001 to p = 0.001). An MRI-radiomics-clinical nomogram incorporating radiomics signature, two prenatal clinical features, and two MRI morphological findings was developed, yielding a higher area under the curve (AUC) than that of the MRI morphological-determined PAS in the training cohort (0.89 vs. 0.78; p < 0.001) and external validation cohort (0.87 vs. 0.75; p = 0.003), while a comparable AUC value in the validation cohort (0.91 vs. 0.81; p = 0.09). The calibration was good. CONCLUSIONS: An MRI-radiomics-clinical nomogram had a robust performance in antenatal predicting the PAS in pregnancies. KEY POINTS: • An MRI-radiomics-clinical-based nomogram might serve as an adjunctive approach for the treatment decision-making in pregnancies suspicious of PAS. • The radiomic score provides a mathematical formula that predicts the possibility of PAS by using the MRI data, and pregnant women with PAS had higher radiomic scores than those without PAS.

Single-incision versus four-incision laparoscopic transfistulous bile duct exploration for Mirizzi syndrome type II.

BACKGROUND: We developed laparoscopic transfistulous bile duct exploration (LTBDE) for Mirizzi syndrome (MS) McSherry type II in September 2011. Then, single-incision LTBDE (SILTBDE) was adopted as a preferred technique since August 2013. This retrospective study aims to analyze the outcome of LTBDE in 7.7 years and to compare SILTBDE with four-incision LTBDE (4ILTBDE). METHODS: Seventeen consecutive patients underwent LTBDE for MS McSherry type II from September 2011 to May 2019. Transfistulous removal of the impacted stone(s), choledochoscopic bile duct exploration, and primary closure of the gallbladder remnant were performed without biliary drainage. RESULTS: The sex ratio is 12:5 (male: female) with an average age of 39.4 ± 10.3 (24-56) years. Ten patients (58.8%) had their diagnoses of MS established by preoperative imaging. According to the Csendes classification, three type II (17.6%), nine type III (52.9%), and five type IV (29.4%) were identified. The operative time was 264.8 ± 60.3 min (156-358 min). The stone clearance rate was 100%. The postoperative hospital stay was 4.7 ± 1.9 (2-10) days. No procedure was converted to an open operation. Two postoperative transient hyperamylasemia (11.8%) and one superficial wound infection (5.9%) occurred and all recovered well under conservative treatment (Clavien-Dindo grade I). During an average 2.2-year follow-up period, no biliary stricture or stone recurrence occurred. No significant difference exists between the SILTBDE and 4ILTBDE groups. Nevertheless, an insignificant trend of shorter postoperative hospital stay was observed in the former. A diagnosis of MS Csendes type IV implicates prolonged total and postoperative hospital stays (p < 0.01). CONCLUSIONS: LTBDE is safe and efficacious for MS McSherry type II. It provides a simple solution for various types of MS and avoids undesirable complications following bilioenteric anastomosis. SILTBDE is comparable to 4ILTBDE for selected patients. Patients with MS Csendes type IV need more time to recover after surgery.

Smartphone-Based Optical Fiber Fluorescence Temperature Sensor.

Optical fiber sensors are one preferred solution for temperature sensing, especially for their capability of real-time monitoring and remote detection. However, many of them still suffer from a huge sensing system and complicated signal demodulate process. In order to solve these problems, we propose a smartphone-based optical fiber fluorescence temperature sensor. All the components, including the laser, filter, fiber coupler, batteries, and smartphone, are integrated into a 3D-printed shell, on the side of which there is a fiber flange used for the sensing probe connection. The fluorescence signal of the rhodamine B solution encapsulated in the sensing probe can be captured by the smartphone camera and extracted into the R value and G value by a self-developed smartphone application. The temperature can be quantitatively measured by the calibrated G/R-temperature relation, which can be unified using the same linear relationship in all solid-liquid-gas environments. The performance verifications prove that the sensor can measure temperature in high accuracy, good stability and repeatability, and has a long conservation time for at least 3 months. The proposed sensor not only can measure the temperature for remote and real-time detection needs, but it is also handheld with a small size of 167 mm × 85 mm × 75 mm supporting on-site applications. It is a potential tool in the temperature sensing field.

Field Evaluation and Calibration of Low-Cost Air Pollution Sensors for Environmental Exposure Research.

This paper seeks to evaluate and calibrate data collected by low-cost particulate matter (PM) sensors in different environments and using different aggregated temporal units (i.e., 5-s, 1-min, 10-min, 30 min intervals). We first collected PM concentrations (i.e., PM1, PM2.5, and PM10) data in five different environments (i.e., indoor and outdoor of an office building, a train platform and lobby of a subway station, and a seaside location) in Hong Kong, using five AirBeam2 sensors as the low-cost sensors and a TSI DustTrak DRX Aerosol Monitor 8533 as the reference sensor. By comparing the collected PM concentrations, we found high linearity and correlation between the data reported by the AirBeam2 sensors in different environments. Furthermore, the results suggest that the accuracy and bias of the PM data reported by the AirBeam2 sensors are affected by rainy weather and environments with high humidity and a high level of hygroscopic salts (i.e., a seaside location). In addition, increasing the aggregation level of the temporal units (i.e., from 5-s to 30 min intervals) increases the correlation between the PM concentrations obtained by the AirBeam2 sensors, while it does not significantly improve the accuracy and bias of the data. Lastly, our results indicate that using a machine learning model (i.e., random forest) for the calibration of PM concentrations collected on sunny days generates better results than those obtained with multiple linear models. These findings have important implications for researchers when designing environmental exposure studies based on low-cost PM sensors.

FOXM1-CD44 Signaling Is Critical for the Acquisition of Regorafenib Resistance in Human Liver Cancer Cells.

Regorafenib is a multikinase inhibitor that was approved by the US Food and Drug administration in 2017. Cancer stem cells (CSCs) are a small subset of cancer-initiating cells that are thought to contribute to therapeutic resistance. The forkhead box protein M1 (FOXM1) plays an important role in the regulation of the stemness of CSCs and mediates resistance to chemotherapy. However, the relationship between FOXM1 and regorafenib resistance in liver cancer cells remains unknown. We found that regorafenib-resistant HepG2 clones overexpressed FOXM1 and various markers of CSCs. Patients with hepatocellular carcinoma also exhibited an upregulation of FOXM1 and resistance to regorafenib, which were correlated with a poor survival rate. We identified a close relationship between FOXM1 expression and regorafenib resistance, which was correlated with the survival of patients with hepatocellular carcinoma. Thus, a strategy that antagonizes FOXM1-CD44 signaling would enhance the therapeutic efficacy of regorafenib in these patients.

Comparison of Manual and Automated Nucleic Acid Extraction Methods in Virus Transport Medium.

BACKGROUND: The implementation of an automated nucleic acid extraction system has many advantages over the manual methods. The purpose of this study was to evaluate the validity of two different methods for nucleic acid extraction in virus transport medium. METHODS: We collected 20 nasopharyngeal swabs in viral transport medium from the emergency department of the Asia University Hospital for the detection of SARS-CoV-2. The performance of the MaelstromTM 8 (Taiwan Advanced Nanotech) and the QIAamp Viral RNA Mini Kit (Qiagen) were compared for the extraction of nucleic acid from viral transport medium. The extracts were used for the validation of the RNA extraction procedures. The RNase P target was amplified in a one-step reverse transcription-quantitative PCR (RT-qPCR) reaction, as internal control for the extraction method. RESULTS: In this study, the agreement between the two methods was good and Pearson's correlation coefficient (r) was 0.919 (p < 0.001). The mean cycle threshold value of the two methods was 29.1. CONCLUSIONS: Overall, the performance values of the MaelstromTM 8 and the QIAamp Viral RNA Mini Kit were comparable to each other. In summary, the MaelstromTM 8 provides a standardized procedure, avoidance of sample-to-sample cross contaminations, is easy to use, improves turnaround time and requires less hands-on time as compared to the manual extraction method. The MaelstromTM 8 is more suitable for clinical laboratories that carry small or medium-sized samples for nucleic acid extraction.

Rapid Cobas Liat SARS-CoV-2 Assay in Comparison with the Laboratory-Developed Real-Time RT-PCR Test.

BACKGROUND: The objective of this study was to compare the validity of two different assays for the detection of SARS-CoV-2. METHODS: We collected 50 nasopharyngeal swabs in universal transport medium from the emergency department of Asia University Hospital for the detection of SARS-CoV-2 using reverse transcription-polymerase chain reaction (RT-PCR). The samples for the Liat SARS-CoV-2 influenza A/B test were stored at -70℃ after SARS-CoV-2 testing using the RT-PCR in order to assess method comparison. RESULTS: In this study, the Limit of detection (LOD) of the cobas Liat SARS-CoV-2 and influenza A/B nucleic acid test is 12 copies/µL and the assay obtained 100% positive agreement and negative percent agreement with RT-PCR. CONCLUSIONS: In summary, a prefect agreement exists between the detection of SARS-CoV-2 conducted with the cobas Liat SARS-CoV-2 and influenza A/B nucleic acid test and the RT-PCR. The cobas Liat SARS-CoV-2 and influenza A/B nucleic acid test is a reliable method for the detection of SARS-CoV-2, and it only requires 20 minutes to obtain the results. On the other hand, the cobas Liat SARS-CoV-2 and influenza A/B nucleic acid test is accurate, easy to use, and provides a faster turnaround time than testing performed in the high-throughput platform.

Heat Transfer and Fluid Flow Characteristics of Microchannel with Oval-Shaped Micro Pin Fins.

A novel microchannel heat sink with oval-shaped micro pin fins (MOPF) is proposed and the characteristics of fluid flow and heat transfer are studied numerically for Reynolds number (Re) ranging from 157 to 668. In order to study the influence of geometry on flow and heat transfer characteristics, three non-dimensional variables are defined, such as the fin axial length ratio (α), width ratio (ß), and height ratio (γ). The thermal enhancement factor (η) is adopted as an evaluation criterion to evaluate the best comprehensive thermal-hydraulic performance of MOPF. Results indicate that the oval-shaped pin fins in the microchannel can effectively prevent the rise of heat surface temperature along the flow direction, which improves the temperature distribution uniformity. In addition, results show that for the studied Reynolds number range and microchannel geometries in this paper, the thermal enhancement factor η increases firstly and then decreases with the increase of α and ß. In addition, except for Re = 157, η decreases first and then increases with the increase of the fin height ratio γ. The thermal enhancement factor for MOPF with α = 4, ß = 0.3, and γ = 0.5 achieves 1.56 at Re = 668. The results can provide a theoretical basis for the design of a microchannel heat exchanger.

A hybrid model combining wavelet transform and recursive feature elimination for running state evaluation of heat-resistant steel using laser-induced breakdown spectroscopy.

Heat-resistant steel is widely used in various industries, and the running state is of great importance for equipment function and safety. In this work, laser-induced breakdown spectroscopy (LIBS) is applied to evaluate the running state of steel using indicators of micro and macro properties. The hybrid model based on wavelet threshold denoising (WTD) and K-fold-support vector machine-recursive feature elimination (K-SVM-RFE) is proposed to estimate the different indictors of various service conditions of steel. Fourteen T91 specimens, including 4 industrial specimens obtained from different service conditions in the power plant boiler, were used as the analytes. Firstly, the noise signal of the LIBS spectra of each specimen was analyzed and removed with WTD. Secondly, an improved approach K-SVM-RFE was applied to select the optimal feature subset and build the classification models of aging grade and hardness grade. The influence of denoising pretreatment on model performance was compared and discussed. Finally, the assessment matrix, established using the indicators from the aging grade and hardness grade, was used to evaluate the running state of steel. The results show that the test assessment matrix obtained with the hybrid model based on WTD and K-SVM-RFE is consistent with the reference matrix on the running state of steel.

Atrial natriuretic peptide inhibits epithelial-mesenchymal transition (EMT) of bronchial epithelial cells through cGMP/PKG signaling by targeting Smad3 in a murine model of allergic asthma.

Background: Atrial natriuretic peptide (ANP) inhibits TGF-ß1-induced epithelial-mesenchymal transition (EMT) in human airway cells. We aim to explore the role and mechanism of ANP on EMT of bronchial epithelial cells from murine model of allergic asthma in vitro. Methods: Murine model of allergic asthma was established with BALB/c mice using ovalbumin (OVA). Bronchial epithelial cells were isolated from OVA-exposed mice, and then were cocultured with TGF-ß1, ANP, natriuretic peptide receptor A antagonist, cGMP analog, cGMP inhibitor or/and protein kinase G (PKG) inhibitor, respectively. We assessed expressions of E-Cadherin, α-SMA, cGMP, Smad3 and p-Smad3 in the murine cells before and after Smad3 silence. Results: Compared with bronchial epithelial cells from controls and OVA-exposed mice without additional stimulation, the mRNA and protein expressions of E-Cadherin were decreased but α-SMA expressions were increased in cells with TGF-ß1 stimulation from OVA-exposed mice in vitro. That could be reversed by ANP. The effect of ANP could be mimicked by the cGMP analog, which could be reversed by cGMP or PKG inhibitor. Moreover, the phosphorylated Smad3 expression was consistent with that of α-SMA. When Smad3 was silenced, Smad3 was mostly expressed in cytoplasm. In contrast, it is mostly expressed in nucleus of non-silenced cells during EMT. Conclusions: In a murine model of allergic asthma, ANP could inhibit TGF-ß1-induced EMT of bronchial epithelial cells through cGMP/PKG signaling, targeting TGF-ß1/Smad3 via attenuating phosphorylation of Smad3 in vitro, which may provide potential of ANP in treating allergic asthma with airway remodeling.

Loss of Glycine N-Methyltransferase Associates with Angiopoietin-Like Protein 8 Expression in High Fat-Diet-Fed Mice.

Imbalance of lipid metabolism is a main cause of metabolic syndrome leading to life-threatening metabolic diseases. Angiopoietin-like protein 8 (Angptl8) was recently identified as a liver and adipose tissue-released hormone that is one of the molecules involved in triglyceride metabolism. However, the regulatory mechanism of Angptl8 is largely unknown. A high fat diet (HFD)-fed mouse model, which showed high cholesterol, high triglyceride, and high insulin in the blood, revealed the upregulation of hepatic and plasma Angptl8 and the downregulation of hepatic glycine N-methyltransferase (GNMT). The inverse correlation of hepatic Angptl8 and GNMT expression in the livers of HFD-fed mice was also confirmed in a publicly available microarray dataset. The mechanistic study using primary hepatocytes showed that the Angptl8 expression could be induced by insulin treatment in a dose- and time-dependent manner. Inhibition of PI3K/Akt pathway by the specific inhibitors or the dominant-negative Akt blocked the insulin-induced Angptl8 expression. Moreover, knockout of GNMT promoted the Akt activation as well as the Angptl8 expression. These results suggested that GNMT might be involved in insulin-induced Angptl8 expression in HFD-mediated metabolic syndrome.