Discrepant soil microbial community and C cycling function responses to conventional and biodegradable microplastics.

Biodegradable microplastics (MPs) are promising alternatives to conventional MPs and are of high global concern. However, their discrepant effects on soil microorganisms and functions are poorly understood. In this study, polyethylene (PE) and polylactic acid (PLA) MPs were selected to investigate the different effects on soil microbiome and C-cycling genes using high-throughput sequencing and real-time quantitative PCR, as well as the morphology and functional group changes of MPs, using scanning electron microscopy and Fourier transform infrared spectroscopy, and the driving factors were identified. The results showed that distinct taxa with potential for MP degradation and nitrogen cycling were enriched in soils with PLA and PE, respectively. PLA, smaller size (150-180 µm), and 5% (w/w) of MPs enhanced the network complexity compared with PE, larger size (250-300 µm), and 1% (w/w) of MPs, respectively. PLA increased ß-glucosidase by up to 2.53 times, while PE (150-180 µm) reduced by 38.26-44.01% and PE (250-300 µm) increased by 19.00-22.51% at 30 days. Amylase was increased by up to 5.83 times by PLA (150-180 µm) but reduced by 40.26-62.96% by PLA (250-300 µm) and 16.11-43.92% by PE. The genes cbbL, cbhI, abfA, and Lac were enhanced by 37.16%- 1.99 times, 46.35%- 26.46 times, 8.41%- 69.04%, and 90.81%- 5.85 times by PLA except for PLA1B/5B at 30 days. These effects were associated with soil pH, NO3--N, and MP biodegradability. These findings systematically provide an understanding of the impact of biodegradable MPs on the potential for global climate change.

[Alzheimer's disease classification based on nonlinear high-order features and hypergraph convolutional neural network].

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder that damages patients' memory and cognitive abilities. Therefore, the diagnosis of AD holds significant importance. The interactions between regions of interest (ROIs) in the brain often involve multiple areas collaborating in a nonlinear manner. Leveraging these nonlinear higher-order interaction features to their fullest potential contributes to enhancing the accuracy of AD diagnosis. To address this, a framework combining nonlinear higher-order feature extraction and three-dimensional (3D) hypergraph neural networks is proposed for computer-assisted diagnosis of AD. First, a support vector machine regression model based on the radial basis function kernel was trained on ROI data to obtain a base estimator. Then, a recursive feature elimination algorithm based on the base estimator was applied to extract nonlinear higher-order features from functional magnetic resonance imaging (fMRI) data. These features were subsequently constructed into a hypergraph, leveraging the complex interactions captured in the data. Finally, a four-dimensional (4D) spatiotemporal hypergraph convolutional neural network model was constructed based on the fMRI data for classification. Experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database demonstrated that the proposed framework outperformed the Hyper Graph Convolutional Network (HyperGCN) framework by 8% and traditional two-dimensional (2D) linear feature extraction methods by 12% in the AD/normal control (NC) classification task. In conclusion, this framework demonstrates an improvement in AD classification compared to mainstream deep learning methods, providing valuable evidence for computer-assisted diagnosis of AD.

Intelligent surgical workflow recognition for endoscopic submucosal dissection with real-time animal study.

Recent advancements in artificial intelligence have witnessed human-level performance; however, AI-enabled cognitive assistance for therapeutic procedures has not been fully explored nor pre-clinically validated. Here we propose AI-Endo, an intelligent surgical workflow recognition suit, for endoscopic submucosal dissection (ESD). Our AI-Endo is trained on high-quality ESD cases from an expert endoscopist, covering a decade time expansion and consisting of 201,026 labeled frames. The learned model demonstrates outstanding performance on validation data, including cases from relatively junior endoscopists with various skill levels, procedures conducted with different endoscopy systems and therapeutic skills, and cohorts from international multi-centers. Furthermore, we integrate our AI-Endo with the Olympus endoscopic system and validate the AI-enabled cognitive assistance system with animal studies in live ESD training sessions. Dedicated data analysis from surgical phase recognition results is summarized in an automatically generated report for skill assessment.

FAFuse: A Four-Axis Fusion framework of CNN and Transformer for medical image segmentation.

Medical image segmentation is crucial for accurate diagnosis and treatment in the medical field. In recent years, convolutional neural networks (CNNs) and Transformers have been frequently adopted as network architectures in medical image segmentation. The convolution operation is limited in modeling long-range dependencies because it can only extract local information through the limited receptive field. In comparison, Transformers demonstrate excellent capability in modeling long-range dependencies but are less effective in capturing local information. Hence, effectively modeling long-range dependencies while preserving local information is essential for accurate medical image segmentation. In this paper, we propose a four-axis fusion framework called FAFuse, which can exploit the advantages of CNN and Transformer. As the core component of our FAFuse, a Four-Axis Fusion module (FAF) is proposed to efficiently fuse global and local information. FAF combines Four-Axis attention (height, width, main diagonal, and counter diagonal axial attention), a multi-scale convolution, and a residual structure with a depth-separable convolution and a Hadamard product. Furthermore, we also introduce deep supervision to enhance gradient flow and improve overall performance. Our approach achieves state-of-the-art segmentation accuracy on three publicly available medical image segmentation datasets. The code is available at https://github.com/cczu-xiao/FAFuse.

Single-Factor Comprehensive Reservoir Quality Classification Evaluation-Taking the Hala'alat Mountains at the Northwestern Margin of the Junggar Basin as an Example.

In the process of petroleum geology exploration and development, reservoir quality evaluation is an essential component. However, conventional reservoir quality evaluation methods are no longer able to provide accurate and comprehensive assessments for all types of reservoirs. Therefore, the comprehensive evaluation of reservoir quality using multiple single factors is of significant importance in improving the level of reservoir quality assessment and enhancing the effectiveness of oil and gas exploration techniques. Conventional reservoir quality evaluation methods can assess only the quality of individual reservoir properties, resulting in limited classification outcomes. Taking the Cretaceous formations in the southern margin of the Hala'alat Mountain in the Junggar Basin as the research object, preliminary classification criteria were established based on the principles of formation coefficient, storage coefficient, and flow unit index. Combining experimental data such as core observation, thin-section identification, pore permeability analysis, and scanning electron microscopy, a comprehensive set of reservoir quality classification and evaluation criteria were developed. Furthermore, the corresponding reservoir classification evaluation maps were generated to illustrate the spatial distribution of reservoir quality. The study reveals that the area can be classified into four types of reservoirs, namely, Class I, Class II, Class III, and Class IV, corresponding to the best reservoir, relatively good reservoir, relatively poor reservoir, and poor reservoir, respectively. Among them, the second (K1q2) and third (K1q3) members of the Cretaceous Qingshuihe Formation, as well as the first (K1h1) and third (K1h3) members of the Cretaceous Hutubi Formation, exhibit the best reservoir quality as Class II. On the other hand, the second member of the Cretaceous Hutubi Formation (K1h2) exhibits the best reservoir quality as Class III, with relatively poorer reservoir quality overall. The research findings of this study can provide an important theoretical basis for oil and gas exploration and development in the region.

Sedimentary Characteristics and Hydrocarbon-Generation Potential of the Permian Pingdiquan Formation in Dongdaohaizi Sag, Junggar Basin, Northwest China.

After several years of extensive exploration, a series of oil and gas reservoirs or structures have been discovered in the Dongdaohaizi sag, situated in the hinterland of the Junggar Basin. However, in recent years, some wells around the sag have failed. Herein, sedimentary facies, the plane distribution of dark mudstone, geochemical characteristics of source rocks, and the control of sedimentary facies on the distribution and development of source rocks in the Permian Pingdiquan Formation in the Dongdaohaizi sag were systematically investigated. A combined geological and geochemical method was used to fully understand the distribution law and resource potential of the source rocks in this area. Investigation results indicate that the Pingdiquan Formation primarily inherited continuous deposition, and the sedimentary facies of the sag, such as semideep lake, shore-shallow lake, prefan delta, fan delta front, and fan delta plain, were developed from the center sag to the outside. The fan delta facies, predominantly distributed in the northern margin of the sag, are characterized by lithology mainly composed of sandy conglomerate and coarse sandstone. The sandstone has a coarse particle size and poor sorting ability, while lacustrine mudstone is widely developed in the sag with a large sedimentary thickness, which is the primary source rock of the Dongdaohaizi sag. The source rocks in the Pingdiquan Formation exhibit medium-to-good quality. The organic matter is categorized as types II1-III, and the thermal evolution maturity is in the mature-high mature stage, indicating a high resource potential. The development of the source rock in the Dongdaohaizi sag is closely related to the sedimentary environment. The sedimentation rate of fan delta facies is high and burial is fast, bringing a large amount of terrestrial organic matter to the lake, thereby increasing the nutrition and organic matter quantity of the lake. Due to the stable water of the lake, low energy at the bottom, and medium conditions of strong reduction, a large amount of organic matter accumulated in the deep to semideep lake facies of the study area, resulting in the development of thick dark mudstone with a thickness of over 400 m. The abundance of organic matter has reached a good level, and the maturity and content of organic matter are high, signifying a high hydrocarbon-generation potential.

Analysis of risk factors for severe acute kidney injury in patients with acute myocardial infarction: A retrospective study.

Background: Patients with acute myocardial infarction (AMI) complicated by acute kidney injury (AKI) tend to have a poor prognosis. However, the exact mechanism of the co-occurrence of the two diseases is unknown. Therefore, this study aims to determine the risk factors for severe AKI in patients with AMI. Methods: A total of 2022 patients were included in the Medical Information Mart for Intensive Care. Variables were identified via univariate logistic regression, and the variables were corrected via multivariate logistic regression. Restricted cubic splines were used to examine the risks associated with the variables. The Kaplan-Meier method was used to compare the risk of severe AKI among the patients. Results: Patients with severe AKI had a higher in-hospital mortality rate (28.6% vs. 9.0%, P < 0.001) and a longer duration of intensive care (6.5 days vs. 2.9 days, P < 0.001). In patients with AMI, the mean systolic blood pressure (SBP); international normalized ratio (INR); the levels of blood urea nitrogen (BUN), glucose, and calcium; and a history of liver disease were found to be the independent risk factors for developing severe AKI after their admission. Increased levels of BUN and blood glucose and a high INR increased the risk of severe AKI; however, increased levels of calcium decreased the risk; SBP presented a U-shaped curve relationship. Conclusions: Patients with severe AKI have a poor prognosis following an episode of AMI. Furthermore, in patients with AMI, SBP; INR; a history of liver disease; and the levels of BUN, glucose, and calcium are the independent risk factors for developing severe AKI after their admission.

Klotho alleviates contrast-induced acute kidney injury by suppressing oxidative stress, inflammation, and NF-KappaB/NLRP3-mediated pyroptosis.

BACKGROUND: Contrast-induced acute kidney injury (CI-AKI) is a common complication following percutaneous coronary intervention in coronary artery disease (CAD) patients with >30% incidence. Klotho is a multifunctional protein that inhibits oxidative stress and inflammation, but its role in CI-AKI is poorly understood. The present study aimed to explore the effects of klotho in CI-AKI. METHODS: Six-week-old mice and HK-2 were divided into the control, contrast medium (CM), CM + klotho, and klotho groups. H&E staining evaluated kidney injury. Scr and BUN showed renal function. DHE probe and ELISA kit detected the levels of reactive oxygen species (ROS) in kidney tissue, superoxide dismutase (SOD), and malondialdehyde (MDA) in serum. Western blot detected the expressions of NF-κB and phosphorylated NF-κB (p-NF-κB) and pyroptosis-related protein levels of NLRP3, caspase-1, GSDMD, and cleaved-GSDMD in the kidney of CI-AKI mice. CCK-8 and lactate dehydrogenase (LDH) activity assays determined cell viability and damage. Fluorescent probe dichloro-dihydro-fluorescein diacetate (DCFH-DA) and enzyme-linked immunosorbent assay (ELISA) tested oxidative stress-related indicators. These included intracellular reactive oxygen species (ROS), superoxidase dismutase (SOD), and malondialdehyde (MDA). IL-6, TNF-α, IL-1ß, and IL-18 in the cell supernatant were tested by ELISA assay and used to reflect inflammation responses. Propidium iodide (PI) staining showed the cell death of HK-2. The expressions of NF-κB, p-NF-κB and pyroptosis-related protein levels of NLRP3, caspase-1, GSDMD, and cleaved-GSDMD were detected by Western blot. RESULTS: Exogenous klotho administration reduced kidney histopathological alterations and improved renal function in vivo. The levels of reactive oxygen species (ROS) in renal tissue, superoxide dismutase (SOD), and malondialdehyde (MDA) in serum decreased after the klotho intervention. The expression levels of p-NF-κB and pyroptosis-related proteins, including NLRP3, caspase-1, GSDMD, and cleaved-GSDMD, were decreased in CI-AKI mice after the klotho intervention. In vitro, klotho significantly inhibited CM-induced oxidative stress and the production of IL-6 and TNF-α. Moreover, it was found that klotho inhibited the activation of p-NF-κB and down-regulated pyroptosis-related protein (NLRP3, caspase-1, GSDMD, and cleaved-GSDMD). CONCLUSION: Klotho has a protective effect on CI-AKI via suppressing oxidative stress, inflammation, and NF-κB/NLRP3-mediated pyroptosis that contributes to the potential therapy of CI-AKI.

CELL INSTANCE SEGMENTATION VIA MULTI-SCALE NON-LOCAL CORRELATION.

For cell instance segmentation on Electron Microscopy (EM) images, state-of-the-art methods either conduct pixel-wise classification or follow a detection and segmentation manner. However, both approaches suffer from the enormous cell instances of EM images where cells are tightly close to each other and show inconsistent morphological properties and/or homogeneous appearances. This fact can easily lead to over-segmentation and under-segmentation problems for model prediction, i.e., falsely splitting and merging adjacent instances. In this paper, we propose a novel approach incorporating non-local correlation in the embedding space to make pixel features distinct or similar to their neighbors and thus address the over- and under-segmentation problems. We perform experiments on five different EM datasets where our proposed method yields better results than several strong baselines. More importantly, by using non-local correlation, we observe fewer false separations within one cell and fewer false fusions between cells.

A High-Accuracy, High Anti-Noise, Unbiased Frequency Estimator Based on Three CZT Coefficients for Deep Space Exploration Mission.

Deep space exploration navigation requires high accuracy of the Doppler measurement, which is equivalent to a frequency estimation problem. Because of the fence effect and spectrum leakage, the frequency estimation performances, which is based on the FFT spectrum methods, are significantly affected by the signal frequency. In this paper, we propose a novel method that utilizes the mathematical relation of the three Chirp-Z Transform (CZT) coefficients around the peak spectral line. The realization, unbiased performance, and algorithm parameter setting rule of the proposed method are described and analyzed in detail. The Monte Carlo simulation results show that the proposed method has a better anti-noise and unbiased performance compared with some traditional estimator methods. Furthermore, the proposed method is utilized to process the raw data of MEX and Tianwen-1 satellites received by Chinese Deep Space Stations (CDSS). The results show that the Doppler estimation accuracy of MEX and Tianwen-1 are both about 3 millihertz (mHz) in 1-s integration, which is consistent with that of ESA/EVN/CDSN and a little better than that of the Chinese VLBI network (CVN). Generally, this proposed method can be effectively utilized to support Chinese future deep space navigation missions and radio science experiments.

DLTTA: Dynamic Learning Rate for Test-Time Adaptation on Cross-Domain Medical Images.

Test-time adaptation (TTA) has increasingly been an important topic to efficiently tackle the cross-domain distribution shift at test time for medical images from different institutions. Previous TTA methods have a common limitation of using a fixed learning rate for all the test samples. Such a practice would be sub-optimal for TTA, because test data may arrive sequentially therefore the scale of distribution shift would change frequently. To address this problem, we propose a novel dynamic learning rate adjustment method for test-time adaptation, called DLTTA, which dynamically modulates the amount of weights update for each test image to account for the differences in their distribution shift. Specifically, our DLTTA is equipped with a memory bank based estimation scheme to effectively measure the discrepancy of a given test sample. Based on this estimated discrepancy, a dynamic learning rate adjustment strategy is then developed to achieve a suitable degree of adaptation for each test sample. The effectiveness and general applicability of our DLTTA is extensively demonstrated on three tasks including retinal optical coherence tomography (OCT) segmentation, histopathological image classification, and prostate 3D MRI segmentation. Our method achieves effective and fast test-time adaptation with consistent performance improvement over current state-of-the-art test-time adaptation methods. Code is available at https://github.com/med-air/DLTTA.

Bioleaching of Chalcopyrite Waste Rock in the Presence of the Copper Solvent Extractant LIX984N.

Heap bioleaching, the solubilization of metal ions from metal sulfides by microbial oxidation, is often combined with solvent extraction (SX) and electrowinning to recover, e.g., copper from low-grade ores. After extraction, the leaching solution is recycled, but the entrained organic solvents may be toxic to the microorganisms. Here Acidithiobacillus ferrooxidans, Leptospirillum ferrooxidans, and Sulfobacillus thermosulfidooxidans were selected to perform bioleaching of chalcopyrite waste rock in the presence of the SX reagent (2.5% v/v LIX984N in kerosene). Possibly inhibitory effects have been evaluated by copper extraction, bacterial activity, number of actively Fe(II)-oxidizing cells, and biofilm formation. Microcalorimetry, most probable number determination, and atomic force microscopy combined with epifluorescence microscopy were applied. The results show that 100 and 300 mg/L SX reagent could hardly inhibit At. ferrooxidans from oxidizing Fe2+, but they seriously interfered with the biofilm formation and the oxidization of sulfur, thereby hindering bioleaching. L. ferrooxidans was sensitive to 50 mg/L SX reagent, which inhibited its bioleaching completely. Sb. thermosulfidooxidans showed different metabolic preferences, if the concentration of the SX reagent differed. With 10 mg/L LIX984N Sb. thermosulfidooxidans preferred to oxidize Fe2+ and extracted the same amount of copper as the assay without LIX984N. With 50 mg/L extractant the bioleaching stopped, since Sb. thermosulfidooxidans preferred to oxidize reduced inorganic sulfur compounds.

Identification of Key Exosome Gene Signature in Mediating Coronary Heart Disease by Weighted Gene Correlation Network Analysis.

BACKGROUND: Coronary heart disease (CHD) is the most prevalent disease with an unelucidated pathogenetic mechanism and is mediated by complex molecular interactions of exosomes. Here, we aimed to identify differentially expressed exosome genes for the disease development and prognosis of CHD. METHOD: Six CHD samples and 32 normal samples were downloaded from the exoRbase database to identify the candidate genes in the CHD. The differentially expressed genes (DEGs) were identified. And then, weighted gene correlation network analysis (WGCNA) was used to investigate the modules in coexpressed genes between CHD samples and normal samples. DEGs and the module of the WGCNA were intersected to obtain the most relevant exosome genes. After that, the function enrichment analyses and protein-protein interaction network (PPI) were performed for the particular module using STRING and Cytoscape software. Finally, the CIBERSORT algorithm was used to analyze the immune infiltration of exosome genes between CHD samples and normal samples. RESULT: We obtain a total of 715 overlapping exosome genes located at the intersection of the DEGs and key modules. The Gene Ontology enrichment of DEGs in the blue module included inflammatory response, neutrophil degranulation, and activation of CHD. In addition, protein-protein networks were constructed, and hub genes were identified, such as LYZ, CAMP, HP, ORM1, and LTF. The immune infiltration profiles varied significantly between normal controls and CHD. Finally, we found that mast cells activated and eosinophils had a positive correlation. B cell memory had a significant negative correlation with B cell naive. Besides, neutrophils and mast cells were significantly increased in CHD patients. CONCLUSION: The underlying mechanism may be related to neutrophil degranulation and the immune response. The hub genes and the difference in immune infiltration identified in the present study may provide new insights into the diagnostic and provide candidate targets for CHD.

Melatonin alleviates lipopolysaccharide-induced myocardial injury by inhibiting inflammation and pyroptosis in cardiomyocytes.

BACKGROUND: Melatonin (MT) has been shown to protect against various cardiovascular diseases. However, the effect of MT on lipopolysaccharide (LPS)-induced myocardial injury is poorly understood. This study aims to evaluate the effects of MT on LPS-induced myocardial injury in vitro. METHODS: H9C2 cells were divided into a control group, MT group, LPS group, and MT + LPS group. The control group was treated with sterile saline solution, the LPS group received 8 µg/mL LPS for 24 h, MT + LPS cells were pretreated with 200 µmol/L MT for 2 h then with 8 µg/mL LPS for 24 h, and the MT group received only 200 µmol/L MT for 2 h. The CCK-8 assay and lactate dehydrogenase (LDH) activity assay were used to analyze cell viability and LDH release, respectively. Intracellular reactive oxygen species (ROS) and the rate of pyroptosis were measured using the fluorescent probe dichloro-dihydro-fluorescein diacetate (DCFH-DA) and propidium iodide (PI) staining, respectively. The cell supernatants were used to measure the levels of inflammatory cytokines, including IL-6, TNF-α, and IL-1ß by enzyme-linked immunosorbent assay (ELISA). The protein levels of iNOS, COX-2, NF-κB, p-NF-κB, NLRP3, caspase-1, and GSDMD were detected by western blot. RESULTS: MT pretreatment significantly improved LPS-induced myocardial injury by inhibiting inflammation and pyroptosis in H9C2 cells. Moreover, MT inhibited the activation of the NF-κB pathway, and reduced the expression of inflammation-related proteins (iNOS and COX-2), and pyroptosis-related proteins (NLRP3, caspase-1, and GSDMD). CONCLUSIONS: Our data suggests that MT can alleviate LPS-induced myocardial injury, providing novel insights into the treatment of sepsis-induced myocardial dysfunction.

Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation.

The invariant development and transparent body of the nematode Caenorhabditis elegans enables complete delineation of cell lineages throughout development. Despite extensive studies of cell division, cell migration and cell fate differentiation, cell morphology during development has not yet been systematically characterized in any metazoan, including C. elegans. This knowledge gap substantially hampers many studies in both developmental and cell biology. Here we report an automatic pipeline, CShaper, which combines automated segmentation of fluorescently labeled membranes with automated cell lineage tracing. We apply this pipeline to quantify morphological parameters of densely packed cells in 17 developing C. elegans embryos. Consequently, we generate a time-lapse 3D atlas of cell morphology for the C. elegans embryo from the 4- to 350-cell stages, including cell shape, volume, surface area, migration, nucleus position and cell-cell contact with resolved cell identities. We anticipate that CShaper and the morphological atlas will stimulate and enhance further studies in the fields of developmental biology, cell biology and biomechanics.

Promoting Earth-Based Radar Astronomical Observations of the Moon.

Earth-based radar astronomical observations provide information on surface characteristics, orbits, and rotations for a wide variety of solar system objects. Based on compound radio telescopes, both the Chinese VLBI (Very Long Baseline Interferometry) network (CVN) and the Russian VLBI network (Quasar), in cooperation with the Chinese radar transmitters, we present the current ground radar astronomical observations of the moon. The spectrum of the reflected radio signals was obtained and the Doppler frequency shift in bi-static radar mode was measured. Radar albedo of the observed region and power ratios of the reflected signals with left- and right-hand circular polarizations were determined, allowing us to study the radar reflectivity and near-surface wavelength-scale roughness of the moon. Future developments on radar astronomy are also discussed in the paper.

Diagnostic accuracy of multi-slice computed tomography in children with Abernethy malformation.

BACKGROUND: Abernethy malformation is a rare congenital abnormality. Imaging examination is an important method for the diagnosis. The purpose of this study was to demonstrate manifestations of multi-slice computed tomography (MSCT) in Abernethy malformation and its diagnostic accuracy. METHODS: Fourteen children with Abernethy malformation were admitted to our center in China between July 2011 and January 2018. All 14 patients (eight males and six females) received MSCT and digital subtraction angiography (DSA) while eight patients also received ultrasound. The patients' age ranged from 1 to 14 (median age 8 years old). The clinical records of the patients were retrospectively reviewed. MSCT raw data were transferred to an Advantage Windows 4.2 or 4.6 workstation (General Electric Medical Systems, Waukesha, WI). We compared the findings of MSCT with DSA and surgical results in order to ascertain diagnostic accuracy. RESULTS: Three cases had type Ib Abernethy malformation and eleven cases had type II. Two cases of type II Abernethy malformation were misdiagnosed as type Ib using MSCT. Comparing the findings of MSCT with DSA and surgical results, the accuracy of MSCT was 85.7% (12/14), in which 100.0% (3/3) were type Ib and 81.8% (9/11) were type II. Clinical information included congenital heart disease, pulmonary hypertension, diffuse pulmonary arteriovenous fistula, abnormal liver function, hepatic nodules, elevated blood ammonia, and hepatic encephalopathy. Eleven cases were treated after diagnosis. One patient with Abernethy malformation type Ib (1/3) underwent liver transplantation. Seven patients with Abernethy malformation type II (7/11) were treated by shunt occlusion, received laparoscopy, or were treated with open surgical ligation. Another three patients (3/11) with Abernethy malformation type II were treated by interventional portocaval shunt occlusion under DSA. CONCLUSION: MSCT attains excellent capability in diagnosing type II Abernethy malformation and further shows the location of the portocaval shunt. DSA can help when it is hard to determine diagnosis between Abernethy type Ib and II using MSCT.

3DMMS: robust 3D Membrane Morphological Segmentation of C. elegans embryo.

BACKGROUND: Understanding the cellular architecture is a fundamental problem in various biological studies. C. elegans is widely used as a model organism in these studies because of its unique fate determinations. In recent years, researchers have worked extensively on C. elegans to excavate the regulations of genes and proteins on cell mobility and communication. Although various algorithms have been proposed to analyze nucleus, cell shape features are not yet well recorded. This paper proposes a method to systematically analyze three-dimensional morphological cellular features. RESULTS: Three-dimensional Membrane Morphological Segmentation (3DMMS) makes use of several novel techniques, such as statistical intensity normalization, and region filters, to pre-process the cell images. We then segment membrane stacks based on watershed algorithms. 3DMMS achieves high robustness and precision over different time points (development stages). It is compared with two state-of-the-art algorithms, RACE and BCOMS. Quantitative analysis shows 3DMMS performs best with the average Dice ratio of 97.7% at six time points. In addition, 3DMMS also provides time series of internal and external shape features of C. elegans. CONCLUSION: We have developed the 3DMMS based technique for embryonic shape reconstruction at the single-cell level. With cells accurately segmented, 3DMMS makes it possible to study cellular shapes and bridge morphological features and biological expression in embryo research.

Observing APOD with the AuScope VLBI Array.

The possibility to observe satellites with the geodetic Very Long Baseline Interferometry (VLBI) technique is vividly discussed in the geodetic community, particularly with regard to future co-location satellite missions. The Chinese APOD-A nano satellite can be considered as a first prototype-suitable for practical observation tests-combining the techniques Satellite Laser Ranging (SLR), Global Navigation Satellite Systems (GNSS) and VLBI on a single platform in a Low Earth Orbit (LEO). Unfortunately, it has hardly been observed by VLBI, so major studies towards actual frame ties could not be performed. The main reason for the lack of observations was that VLBI observations of satellites are non-standard, and suitable observing strategies were not in place for this mission. This work now presents the first serious attempt to observe the satellite with a VLBI network over multiple passes. We introduce a series of experiments with the AuScope geodetic VLBI array which were carried out in November 2016, and describe all steps integrated in the established process chain: the experiment design and observation planning, the antenna tracking and control scheme, correlation and derivation of baseline-delays, and the data analysis yielding delay residuals on the level of 10 ns. The developed procedure chain can now serve as reference for future experiments, hopefully enabling the global VLBI network to be prepared for the next co-location satellite mission.

Primitive neuroectodermal tumor originating from the lung: A case report.

Primitive neuroectodermal tumors (PNETs) are small, round cell tumors that may be classified as peripheral or central, based on their site of origin. PNETs often arise in the soft tissue or bone of young adults. Although not common, PNETs have been described in other organs, including the gonads, kidneys, myocardium and pancreas, but rarely in the lungs without chest wall or pleural involvement. The present study reports a rare case of peripheral PNET (pPNET), which originated in the lung. A 37-year-old female patient presented at Xuzhou Central Hospital (Xuzhou, China) with a history of a dry cough, mild dyspnea and slight pain in the left chest. Histopathological and immunohistochemical analyses permitted the diagnosis of a pPNET. The patient was treated with surgical resection, followed by chemotherapy (including cyclophosphamide, cisplatin and vincristine), radiotherapy and traditional Chinese medicine (including Kanglaite and Shenqi Fuzheng injections). At the time of writing, the patient was alive with no sign of recurrence and under regular follow-ups at the Outpatient Clinic of Xuzhou Central Hospital.