Automatic segmentation of hepatocellular carcinoma on dynamic contrast-enhanced MRI based on deep learning

Objective. Precise hepatocellular carcinoma (HCC) detection is crucial for clinical management. While studies focus on computed tomography-based automatic algorithms, there is a rareness of research on automatic detection based on dynamic contrast enhanced (DCE) magnetic resonance imaging. This study is to develop an automatic detection and segmentation deep learning model for HCC using DCE.Approach: DCE images acquired from 2016 to 2021 were retrospectively collected. Then, 382 patients (301 male; 81 female) with 466 lesions pathologically confirmed were included and divided into an 80% training-validation set and a 20% independent test set. For external validation, 51 patients (42 male; 9 female) in another hospital from 2018 to 2021 were included. The U-net architecture was modified to accommodate multi-phasic DCE input. The model was trained with the training-validation set using five-fold cross-validation, and furtherly evaluated with the independent test set using comprehensive metrics for segmentation and detection performance. The proposed automatic segmentation model consisted of five main steps: phase registration, automatic liver region extraction using a pre-trained model, automatic HCC lesion segmentation using the multi-phasic deep learning model, ensemble of five-fold predictions, and post-processing using connected component analysis to enhance the performance to refine predictions and eliminate false positives.Main results. The proposed model achieved a mean dice similarity coefficient (DSC) of 0.81 ± 0.11, a sensitivity of 94.41 ± 15.50%, a precision of 94.19 ± 17.32%, and 0.14 ± 0.48 false positive lesions per patient in the independent test set. The model detected 88% (80/91) HCC lesions in the condition of DSC > 0.5, and the DSC per tumor was 0.80 ± 0.13. In the external set, the model detected 92% (58/62) lesions with 0.12 ± 0.33 false positives per patient, and the DSC per tumor was 0.75 ± 0.10.Significance.This study developed an automatic detection and segmentation deep learning model for HCC using DCE, which yielded promising post-processed results in accurately identifying and delineating HCC lesions.

Joint learning framework of cross-modal synthesis and diagnosis for Alzheimer's disease by mining underlying shared modality information

Alzheimer's disease (AD) is one of the most common neurodegenerative disorders presenting irreversible progression of cognitive impairment. How to identify AD as early as possible is critical for intervention with potential preventive measures. Among various neuroimaging modalities used to diagnose AD, functional positron emission tomography (PET) has higher sensitivity than structural magnetic resonance imaging (MRI), but it is also costlier and often not available in many hospitals. How to leverage massive unpaired unlabeled PET to improve the diagnosis performance of AD from MRI becomes rather important. To address this challenge, this paper proposes a novel joint learning framework of unsupervised cross-modal synthesis and AD diagnosis by mining underlying shared modality information, improving the AD diagnosis from MRI while synthesizing more discriminative PET images. We mine underlying shared modality information in two aspects: diversifying modality information through the cross-modal synthesis network and locating critical diagnosis-related patterns through the AD diagnosis network. First, to diversify the modality information, we propose a novel unsupervised cross-modal synthesis network, which implements the inter-conversion between 3D PET and MRI in a single model modulated by the AdaIN module. Second, to locate shared critical diagnosis-related patterns, we propose an interpretable diagnosis network based on fully 2D convolutions, which takes either 3D synthesized PET or original MRI as input. Extensive experimental results on the ADNI dataset show that our framework can synthesize more realistic images, outperform the state-of-the-art AD diagnosis methods, and have better generalization on external AIBL and NACC datasets.

A CT-based radiomics integrated model for discriminating pulmonary cryptococcosis granuloma from lung adenocarcinoma-a diagnostic test

Background

Chest computed tomography (CT) is a critical tool in the diagnosis of pulmonary cryptococcosis as approximately 30% of normal immunity individuals may not exhibit any significant symptoms or laboratory findings. Pulmonary cryptococcosis granuloma and lung adenocarcinoma can appear similar on noncontrast chest CT. This study evaluates the use of an integrated model that was developed based on radiomic features combined with demographic and radiological features to differentiate pulmonary cryptococcosis nodules from lung adenocarcinomas.

Methods

Preoperative chest CT images for 215 patients with solid pulmonary nodules with histopathologically confirmed lung adenocarcinoma and cryptococcosis infection were collected from two clinical centers (108 cases in the training set and 107 cases in the test set divided by the different hospitals). Radiomics models were constructed based on nodular lesion volume (LV), 5-mm extended lesion volume (ELV), and perilesion volume (PLV). A demoradiological model was constructed using logistic regression based on demographic information (age, sex) and 12 radiological features (location, number, shape and specific imaging signs). Both models were used to build an integrated model, the performance of which was assessed using the test set. A junior and a senior radiologist evaluated the nodules. Receiver operating characteristic (ROC) curve analysis was conducted, and areas under the curve (AUCs), sensitivity (SEN), and specificity (SPE) of the models were calculated and compared.

Results

Among the radiomics models, AUCs of the LV, ELV, and PLV were 0.558, 0.757, and 0.470, respectively. Age, lesion number, and lobular sign were identified as independent discriminative features providing an AUC of 0.77 in the demoradiological model (SEN 0.815, SPE 0.642). The integrated model achieved the highest AUC of 0.801 (SEN 0.759, SPE 0.755), which was significantly higher than that obtained by a junior radiologist (AUC =0.689, P=0.024) but showed no significant difference from that of the senior radiologist (AUC =0.784, P=0.388).

Conclusions

An integrated model with radiomics and demoradiological features improves discrimination of cryptococcosis granulomas from solid adenocarcinomas on noncontrast CT. This model may be an effective strategy for machine complementation to discrimination by radiologists, and whole-lung automated recognition methods might dominate in the future.

Modular Level Alterations Of Structural-Functional Connectivity Coupling in Mild Cognitive Impairment Patients and Interactions with Age Effect

BACKGROUND

Structural-functional connectivity (SC- FC) coupling is related to various cognitive functions and more sensitive for the detection of subtle brain alterations.

OBJECTIVE

To investigate whether decoupling of SC-FC was detected in mild cognitive impairment (MCI) patients on a modular level, the interaction effect of aging and disease, and its relationship with network efficiency.

METHODS

73 patients with MCI and 65 healthy controls were enrolled who underwent diffusion tensor imaging and resting-state functional MRI to generate structural and functional networks. Five modules were defined based on automated anatomical labeling 90 atlas, including default mode network (DMN), frontoparietal attention network (FPN), sensorimotor network (SMN), subcortical network (SCN), and visual network (VIS). Intra-module and inter-module SC-FC coupling were compared between two groups. The interaction effect of aging and group on modular SC-FC coupling was further analyzed by two-way ANOVA. The correlation between the coupling and network efficiency was finally calculated.

RESULTS

In MCI patients, aberrant intra-module coupling was noted in SMN, and altered inter-module coupling was found in the other four modules. Intra-module coupling exhibited significant age-by-group effects in DMN and SMN, and inter-module coupling showed significant age-by-group effects in DMN and FPN. In MCI patients, both positive or negative correlations between coupling and network efficiency were found in DMN, FPN, SCN, and VIS.

CONCLUSION

SC-FC coupling could reflect the association of SC and FC, especially in modular levels. In MCI, SC-FC coupling could be affected by the interaction effect of aging and disease, which may shed light on advancing the pathophysiological mechanisms of MCI.

Brain MRI features of anti-N-methyl-D-aspartate (anti-NMDA) receptor encephalitis secondary to central nervous system infection in adult patients

BACKGROUND

Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis secondary to central nervous system (CNS) infection is a unique subtype of the autoimmune-mediated disease, of which the imaging features are unclear.

PURPOSE

To compare the brain magnetic resonance imaging (MRI) features between the anti-NMDAR encephalitis secondary to CNS infection and that without initial infection.

MATERIAL AND METHODS

A total of 70 adult patients with anti-NMDAR encephalitis were retrospectively enrolled (24 in the post-infection group, 46 in the non-infection-related group). Their clinical and imaging features (lesion distribution, lesion shape, enhancement pattern, brain atrophy) were reviewed and summarized. Lesion distributions were compared between the two groups on lesion probability maps.

RESULTS

The patients with normal brain MRI scans in the post-infection group were less than those in the non-infection related group (29% vs. 63%; P = 0.0113). Among the 24 patients in the post-infection group, visible lesions were shown at the anti-NMDAR encephalitis onset in 17 patients; lesion distribution was more diffuse than the non-infection-related group, showing higher lesion peak probabilities in the bilateral hippocampus, frontal lobe, temporal lobe, insula, and cingulate. The lesions with contrast enhancement were also more common in the post-infection group than the non-infection-related group (7/13 vs. 2/10). Brain atrophy was observed in eight patients in the post-infection group and three in the non-infection-related group.

CONCLUSION

Anti-NMDAR encephalitis secondary to CNS infection has its imaging features-extensive lesion distribution, leptomeningeal enhancement, early atrophy, and necrosis-that could deepen the understanding of the pathophysiology and manifestation of the autoimmune encephalitis besides the classic type.

Iron quantitative analysis of motor combined with bulbar region in M1 cortex may improve diagnosis performance in ALS

OBJECTIVES

To explore whether the combined analysis of motor and bulbar region of M1 on susceptibility-weighted imaging (SWI) can be a valid biomarker for amyotrophic lateral sclerosis (ALS).

METHODS

Thirty-two non-demented ALS patients and 35 age- and gender-matched healthy controls (HC) were retrospectively recruited. SWI and 3D-T1-MPRAGE images were obtained from all individuals using a 3.0-T MRI scan. The bilateral posterior band of M1 was manually delineated by three neuroradiologists on phase images and subdivided into the motor and bulbar regions. We compared the phase values in two groups and performed a stratification analysis (ALSFRS-R score, duration, disease progression rate, and onset). Receiver operating characteristic (ROC) curves were also constructed.

RESULTS

ALS group showed significantly increased phase values in M1 and the two subregions than the HC group, on the all and elderly level (p < 0.001, respectively). On all-age level comparison, negative correlations were found between phase values of M1 and clinical score and duration (p < 0.05, respectively). Similar associations were found in the motor region (p < 0.05, respectively). On both the total (p < 0.01) and elderly (p < 0.05) levels, there were positive relationships between disease progression rate and M1 phase values. In comparing ROC curves, the entire M1 showed the best diagnostic performance.

CONCLUSIONS

Combining motor and bulbar analyses as an integral M1 region on SWI can improve ALS diagnosis performance, especially in the elderly. The phase value could be a valuable biomarker for ALS evaluation.

KEY POINTS

• Integrated analysis of the motor and bulbar as an entire M1 region on SWI can improve the diagnosis performance in ALS. • Quantitative analysis of iron deposition by SWI measurement helps the clinical evaluation, especially for the elderly patients. • Phase value, when combined with the disease progression rate, could be a valuable biomarker for ALS.

A novel cascade machine learning pipeline for Alzheimer's disease identification and prediction

Introduction

Alzheimer's disease (AD) is a progressive and irreversible brain degenerative disorder early. Among all diagnostic strategies, hippocampal atrophy is considered a promising diagnostic method. In order to proactively detect patients with early Alzheimer's disease, we built an Alzheimer's segmentation and classification (AL-SCF) pipeline based on machine learning.

Methods

In our study, we collected coronal T1 weighted images that include 187 patients with AD and 230 normal controls (NCs). Our pipeline began with the segmentation of the hippocampus by using a modified U2-net. Subsequently, we extracted 851 radiomics features and selected 37 features most relevant to AD by the Hierarchical clustering method and Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. At last, four classifiers were implemented to distinguish AD from NCs, and the performance of the models was evaluated by accuracy, specificity, sensitivity, and area under the curve.

Results

Our proposed pipeline showed excellent discriminative performance of classification with AD vs NC in the training set (AUC=0.97, 95% CI: (0.96-0.98)). The model was also verified in the validation set with Dice=0.93 for segmentation and accuracy=0.95 for classification.

Discussion

The AL-SCF pipeline can automate the process from segmentation to classification, which may assist doctors with AD diagnosis and develop individualized medical plans for AD in clinical practice.

An MRI-based joint model of radiomics and spatial distribution differentiates autoimmune encephalitis from low-grade diffuse astrocytoma

BACKGROUND

The differential diagnosis between autoimmune encephalitis and low-grade diffuse astrocytoma remains challenging. We aim to develop a quantitative model integrating radiomics and spatial distribution features derived from MRI for discriminating these two conditions.

METHODS

In our study, we included 188 patients with confirmed autoimmune encephalitis (n = 81) and WHO grade II diffuse astrocytoma (n = 107). Patients with autoimmune encephalitis (AE, n = 59) and WHO grade II diffuse astrocytoma (AS, n = 79) were divided into training and test sets, using stratified sampling according to MRI scanners. We further included an independent validation set (22 patients with AE and 28 patients with AS). Hyperintensity fluid-attenuated inversion recovery (FLAIR) lesions were segmented for each subject. Ten radiomics and eight spatial distribution features were selected via the least absolute shrinkage and selection operator (LASSO), and joint models were constructed by logistic regression for disease classification. Model performance was measured in the test set using the area under the receiver operating characteristic (ROC) curve (AUC). The discrimination performance of the joint model was compared with neuroradiologists.

RESULTS

The joint model achieved better performance (AUC 0.957/0.908, accuracy 0.914/0.840 for test and independent validation sets, respectively) than the radiomics and spatial distribution models. The joint model achieved lower performance than a senior neuroradiologist (AUC 0.917/0.875) but higher performance than a junior neuroradiologist (AUC 0.692/0.745) in the test and independent validation sets.

CONCLUSION

The joint model of radiomics and spatial distribution from a single FLAIR could effectively classify AE and AS, providing clinical decision support for the differential diagnosis between the two conditions.

A coarse-to-fine cascade deep learning neural network for segmenting cerebral aneurysms in time-of-flight magnetic resonance angiography

BACKGROUND

Accurate segmentation of unruptured cerebral aneurysms (UCAs) is essential to treatment planning and rupture risk assessment. Currently, three-dimensional time-of-flight magnetic resonance angiography (3D TOF-MRA) has been the most commonly used method for screening aneurysms due to its noninvasiveness. The methods based on deep learning technologies can assist radiologists in achieving accurate and reliable analysis of the size and shape of aneurysms, which may be helpful in rupture risk prediction models. However, the existing methods did not accomplish accurate segmentation of cerebral aneurysms in 3D TOF-MRA.

METHODS

This paper proposed a CCDU-Net for segmenting UCAs of 3D TOF-MRA images. The CCDU-Net was a cascade of a convolutional neural network for coarse segmentation and the proposed DU-Net for fine segmentation. Especially, the dual-channel inputs of DU-Net were composed of the vessel image and its contour image which can augment the vascular morphological information. Furthermore, a newly designed weighted loss function was used in the training process of DU-Net to promote the segmentation performance.

RESULTS

A total of 270 patients with UCAs were enrolled in this study. The images were divided into the training (N = 174), validation (N = 43), and testing (N = 53) cohorts. The CCDU-Net achieved a dice similarity coefficient (DSC) of 0.616 ± 0.167, Hausdorff distance (HD) of 5.686 ± 7.020 mm, and volumetric similarity (VS) of 0.752 ± 0.226 in the testing cohort. Compared with the existing best method, the DSC and VS increased by 18% and 5%, respectively, while the HD decreased by one-tenth.

CONCLUSIONS

We proposed a CCDU-Net for segmenting UCAs in 3D TOF-MRA, and the obtained results show that the proposed method outperformed other existing methods.

Multi-lesion radiomics model for discrimination of relapsing-remitting multiple sclerosis and neuropsychiatric systemic lupus erythematosus

OBJECTIVES

To develop an MRI-based multi-lesion radiomics model for discrimination of relapsing-remitting multiple sclerosis (RRMS) and its mimicker neuropsychiatric systemic lupus erythematosus (NPSLE).

METHODS

A total of 112 patients with RRMS (n = 63) or NPSLE (n = 49) were assigned to training and test sets with a ratio of 3:1. All lesions across the whole brain were manually segmented on T2-weighted fluid-attenuated inversion recovery images. For each single lesion, 371 radiomics features were extracted and trained using machine learning algorithms, producing Radiomics Index for Lesion (RIL) for each lesion and a single-lesion radiomics model. Then, for each subject, single lesions were assigned to one of two disease courts based on their distance to decision threshold, and a Radiomics Index for Subject (RIS) was calculated as the mean RIL value of lesions on the higher-weighted court. Accordingly, a subject-level discrimination model was constructed and compared with performances of two radiologists.

RESULTS

The subject-based discrimination model satisfactorily differentiated RRMS and NPSLE in both training (AUC = 0.967, accuracy = 0.892, sensitivity = 0.917, and specificity = 0.872) and test sets (AUC = 0.962, accuracy = 0.931, sensitivity = 1.000, and specificity = 0.875), significantly better than the single-lesion radiomics method (training: p < 0.001; test: p = 0.001) Besides, the discrimination model significantly outperformed the senior radiologist in the training set (training: p = 0.018; test: p = 0.077) and the junior radiologist in both the training and test sets (training: p = 0.008; test: p = 0.023).

CONCLUSIONS

The multi-lesion radiomics model could effectively discriminate between RRMS and NPSLE, providing a supplementary tool for accurate differential diagnosis of the two diseases.

KEY POINTS

• Radiomic features of brain lesions in RRMS and NPSLE were different. • The multi-lesion radiomics model constructed using a merging strategy was comprehensively superior to the single-lesion-based model for discrimination of RRMS and NPSLE. • The RRMS-NPSLE discrimination model showed a significantly better performance or a trend toward significance than the radiologists.

Alterations of spontaneous brain activity in systematic lupus erythematosus patients without neuropsychiatric symptoms: A resting-functional MRI study

PURPOSE

To explore the alterations of spontaneous neuronal activity using amplitude of low-frequency fluctuation (ALFF), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) in non-NPSLE patients and their relationship with the anxiety and depression statuses.

METHODS

Twenty-three non-NPSLE patients and 28 healthy controls were enrolled in this study. Resting-state functional magnetic resonance imaging was firstly analyzed by ALFF, fALFF, and ReHo. The relationships between ALFF/fALFF/ReHo values of abnormal regions and anxiety/depression rating scales, including Self-Rating Anxiety (SAS) and Self-Rating Depression (SDS), were also analyzed.

RESULTS

Compared with HC, non-NPSLE had decreased ALFF values in the bilateral postcentral gyrus, while increased ALFF values in the bilateral inferior temporal gyrus, left putamen, and bilateral precuneus. Non-NPSLE showed reduced fALFF values in the left lingual gyrus, left middle occipital gyrus, right postcentral gyrus, and left superior parietal gyrus, while increased fALFF values were in the left inferior temporal gyrus, right hippocampus, bilateral precuneus, and bilateral superior frontal gyrus. Reduced ReHo values were in the bilateral postcentral gyrus and higher ReHo values were in the left inferior temporal gyrus, left putamen, and bilateral superior frontal gyrus. In the non-NPSLE group, the mean ALFF values of bilateral precuneus were positively correlated with the SAS rating scales (R = 0.5519, p = 0.0176); either were the mean ALFF values of right inferior temporal gyrus and SAS rating scales (R = 0.5380, p = 0.0213). The mean fALFF values of left inferior temporal gyrus were positively correlated with SAS rating scales (R = 0.5700, p = 0.0135). And the mean ReHo values of left putamen were positively correlated with SDS (R = 0.5477, p = 0.0186).

CONCLUSION

Non-NPSLE exhibited abnormal spontaneous neural activity and coherence in several brain regions mainly associated with cognitive and emotional functions. The ALFF values of bilateral PCUN, the right ITG, the fALFF values of left ITG, and the ReHo values of left PUT may be complementary biomarkers for assessing the psychiatric symptoms.

Swallow tail sign on susceptibility map-weighted imaging (SMWI) for disease diagnosing and severity evaluating in parkinsonism

BACKGROUND

Loss of swallow tail sign (STS) on iron-sensitive magnetic resonance imaging (MRI) has been recognized as an imaging feature in parkinsonism (PS).

PURPOSE

To investigate the diagnostic and differential diagnostic value of STS scale on susceptibility map-weighted imaging (SMWI) in PS, including Parkinson's disease (PD), progressive supranuclear palsy syndrome (PSP), and multiple system atrophy (MSA), and to evaluate its correlation with disease severity.

MATERIAL AND METHODS

Ninety-nine patients (55 PD, 29 PSP, and 15 MSA) and 47 healthy controls (HC) were prospectively recruited and scanned using quantitative susceptibility mapping (QSM). STS was visually assessed on SMWI derived from QSM. STS scale in the range of 0-4 at participant level was calculated by summing bilateral STS scores (0-2). We used receiver operating characteristic analysis of STS scale for evaluating the diagnostic power of parkinsonism and Spearman's correlation for assessing disease severity.

RESULTS

Frequency distribution of STS scale was significantly different in parkinsonism and HC groups, and among PD, PSP, and MSA subgroups. STS scale ≤3 could distinguish parkinsonism from HC with high accuracy (91.78%), PD from HC (91.18%), and MSA from HC (88.71%). STS scale ≤2 could distinguish PSP from HC (96.05%). STS scale = 0 could distinguish PSP from PD (70.24%) and PSP from MSA (72.73%). STS scale was negatively correlated with H-Y stage (P = 0.007, r = -0.359) and duration of disease (P = 0.006, r = -0.367) in PD patients.

CONCLUSION

STS scale on SMWI may serve as a useful imaging biomarker for diagnosis of parkinsonism and disease progression evaluation in PD.

[Effects of trabecular metal augments for the reconstruction of Paprosky type Ⅲ acetabulum bone defects]

Objective: To investigate the methods and short-time clinical results of reconstruction of Paprosky type Ⅲ acetabulum bone defects by using tantalum augments. Methods: A total of 17 patients (17 hips) with Paprosky type Ⅲ acetabulum bone defects, treated with tantalum augments in revision of total hip arthroplasty at Department of Orthopedics Surgery in General Hospital of Chinese People's Liberation Army were retrospectively analyzed from March 2014 to May 2016.There were 6 males and 11 females aged from 23 to 74 years with an average of (50.2±16.3) years. Tantalum augments or TM-Cup augment (the cup-on-cup technique) were used to reconstruct the defects.The TM-Cup augment was the tantalum revision cup which was removed titanium ring. The cup-on-cup technique combined TM-Cup augment and biological acetabulum cup. Augments were served as the nonresorptive structural allograft in revision of total hip arthroplasty. Harris hip score was used to evaluate clinical effects. The vertical position of the rotation center was measured and analyzed. Radiographic assessments of the acetabular components were performed by DeLee-Charnley and the Anderson criteria and recorded postoperative complications. Results: All the patients were followed up from 3 to 29 months with an average of (16.2±5.4) months, tantalum augments and biological acetabulum cup were used in 13 patients, the TM-Cup augment and biological acetabulum cup were used in 4 patients. At the time of the latest follow-up, the mean Harris hip score increased compared to preoperatively (86.8±8.3 vs. 30.0±12.0) (t=12.78, P<0.01), the average vertical location of the center of rotation was decreased ((25.3±9.8) mm vs.(47.6±10.5)) mm (t=4.95, P<0.01). All the tantalum augments and biological acetabulum cups were stable, there were no infection, dislocation and other complications. Conclusions: The use of tantalum augments could be considered as an effective management of Paprosky type Ⅲ defects providing good clinical and radiographic outcomes in the short term.The cup-on-cup technique which was used in reconstruction of severe superior-invagination acetabular bone defects and restoration relatively normal center of rotation had special application value.

Wetting behavior and nanotribological properties of silicon nanopatterns combined with diamond-like carbon and perfluoropolyether films

A large number of silicon (Si) patterns consisting of nanopillars of varying diameter and pitch have been fabricated and further coated with diamond-like carbon (DLC) and perfluoropolyether (Z-DOL) films. The wetting behavior and nano-adhesion/friction of the patterns are investigated experimentally in relation to the nanostructures and the hydrophobicity of the materials. Measurements of water contact angle illustrate that the patterning-enhanced wettability of the Si flat surface, along with two distinct wettings which are in good agreement with the Wenzel and hemi-wicking states, depended on the value of the pitch-over-diameter ratio. In the case of the coated patterns, three wetting states are observed: the Cassie-Baxter, the Wenzel, and a transition from the Cassie-Baxter into the Wenzel, which varies with regard to the hydrophobic properties of the DLC and Z-DOL. In terms of tribological properties, it is demonstrated that a combination of the nanopatterns and the films is effective in reducing adhesive and frictional forces. In addition, the pitch and diameter of the patterns are found to significantly influence their adhesion/friction behaviors.

Role of CK1 in GSK3beta-mediated phosphorylation and degradation of snail

The epithelial to mesenchymal transition (EMT) that occurs during embryonic development has begun to attract attention as a potential mechanism for tumor cell metastasis. Snail is a well-known Zn-finger transcription factor that promotes EMT by repressing E-cadherin expression. It is known that Snail is phosphorylated by GSK3beta and degraded by beta-TrCP-mediated ubiquitination. Here we described another protein kinase, CK1, whose phosphorylation of Snail is required for the subsequent GSK3beta phosphorylation. Specific inhibition or depletion of CK1varepsilon inhibits the phosphorylation and degradation of Snail and promotes cell migration, suggesting a central role of CK1varepsilon in the EMT process. Furthermore, our study uncovered distinct roles and steps of Snail phosphorylation by CK1varepsilon and GSK3beta. Taken together, we identified CK1varepsilon as a new component of the Snail-mediated EMT process, providing insight into the mechanism of human cancer metastasis.

Separation and quantitation of phospholipids and their ether analogues by high-performance liquid chromatography

The common mobile phase hexane/isopropanol/water used for separation of phospholipids on high-performance liquid chromatography silica columns poses several problems, such as incomplete separation and rapid column deterioration. By inclusion of 5 mM ammonium sulfate in the aqueous phase, we were able to substantially improve the chromatographic resolution and obtain complete separation of phosphatidylcholine, phosphatidylethanolamine, lysophosphatidylcholine, lysophosphatidylethanolamine, phosphatidylserine, phosphatidylinositol, cardiolipin, phosphatidylglycerol, and sphingomyelin. In addition, ammonium sulfate prevented column degeneration and greatly improved reproducibility. A new quantitation method for alkenylacyl, alkylacyl, and diacyl forms of phospholipids was also developed based on derivatization with [(3)H]acetic anhydride. Separation and quantitation of the radioactive acetyl diradylglycerols were performed by straight-phase HPLC coupled to a radioactive flow detector and enabled detection of the various ether analogues at the picomole level with high reproducibility. The described methods are mild and nondestructive and can therefore be easily combined with analysis of either molecular species or fatty acid and aldehyde composition of the individual phospholipids.

Ascorbate attenuates atrial pacing-induced peroxynitrite formation and electrical remodeling and decreases the incidence of postoperative atrial fibrillation

Atrial fibrillation (AF), the most common chronic arrhythmia, increases the risk of stroke and is an independent predictor of mortality. Available pharmacological treatments have limited efficacy. Once initiated, AF tends to self-perpetuate, owing in part to electrophysiological remodeling in the atria; however, the fundamental mechanisms underlying this process are still unclear. We have recently demonstrated that chronic human AF is associated with increased atrial oxidative stress and peroxynitrite formation; we have now tested the hypothesis that these events participate in both pacing-induced atrial electrophysiological remodeling and in the occurrence of AF following cardiac surgery. In chronically instrumented dogs, we found that rapid (400 min(-1)) atrial pacing was associated with attenuation of the atrial effective refractory period (ERP). Treatment with ascorbate, an antioxidant and peroxynitrite decomposition catalyst, did not directly modify the ERP, but attenuated the pacing-induced atrial ERP shortening following 24 to 48 hours of pacing. Biochemical studies revealed that pacing was associated with decreased tissue ascorbate levels and increased protein nitration (a biomarker of peroxynitrite formation). Oral ascorbate supplementation attenuated both of these changes. To evaluate the clinical significance of these observations, supplemental ascorbate was given to 43 patients before, and for 5 days following, cardiac bypass graft surgery. Patients receiving ascorbate had a 16.3% incidence of postoperative AF, compared with 34.9% in control subjects. In combination, these studies suggest that oxidative stress underlies early atrial electrophysiological remodeling and offer novel insight into the etiology and potential treatment of an enigmatic and difficult to control arrhythmia. The full text of this article is available at http://www.circresaha.org.

Immunotoxicity of N,N-diethylaniline in mice: effect on natural killer activity, cytotoxic T lymphocyte activity, lymphocyte proliferation response and cellular components of the spleen

We previously found that N,N-diethylaniline increased the frequency of sister chromatid exchange (SCE) of human lymphocytes to about five times that of the control value, and was as toxic as cyclophosphamide used as a positive control for SCE. To explore whether N,N-diethylaniline affects the function of lymphocytes, we evaluated its immunotoxicity using CBA/N mice. The mice were divided into four groups and received 0, 100, 200, or 400 mg/kg body weight of N,N-diethylaniline by subcutaneous injection. The following items were investigated on days 3 and 7 after injection: body weight, weight of spleen, number of splenocytes, natural killer (NK) and cytotoxic T lymphocyte (CTL) activities, and concanavalin A (Con A)- and lipopolysaccharide (LPS)-stimulated lymphocyte proliferation using splenocytes. The following splenocyte phenotypes were also quantified by flow cytometry: (1) B cells; (2) total T cells; (3) CD4(+) and CD8(+) T cells; (4) NK; (5) macrophages and (6) nucleated erythrocytes. The splenic NK and CTL activities in exposed groups significantly decreased compared to the control in a dose-dependent manner and lymphocytes from the 200 and 400 mg/kg groups showed significantly higher spontaneous proliferation. The weight of the spleen and number of splenocytes were significantly higher in exposed groups than in the control. N,N-Diethylaniline also increased the percentages of macrophages, nucleated erythrocytes and B cells in the spleen. On the other hand, N,N-diethylaniline did not affect LPS-stimulated B cell and Con A-stimulated T cell proliferation, or the percentages of NK, total T, and CD4(+) and CD8(+) T cells in the spleen or the body weight of mice. The above findings indicated that N,N-diethylaniline selectively inhibited splenic NK and CTL activity and this inhibition was due to decreased NK and CTL functions, but not due to changes in the numbers of splenic NK and T cells.

The by-products generated during sarin synthesis in the Tokyo sarin disaster induced inhibition of natural killer and cytotoxic T lymphocyte activity

More than 5000 passengers on Tokyo subway trains were injured by the nerve gas, sarin and its by-products. Analysis of phosphor-carrying metabolites of sarin and its by-products in urine samples from the victims suggested that they were exposed not only to sarin, but also by-products generated during sarin synthesis, i.e. diisopropyl methylphosphonate (DIMP) and diethyl methylphosphonate (DEMP). We suspected genetic after-effects due to sarin by-products, thus, we checked the frequency of sister chromatid exchange (SCE) and found that SCE was significantly higher in the victims than in a control group, and that DIMP and DEMP significantly induced human lymphocyte SCE in vitro. In the present study, to explore whether DIMP and DEMP, which induced a high frequency of SCE of lymphocytes, also affected the lymphocyte functions, we examined the effect of DIMP and DEMP on splenic natural killer (NK) and splenic cytotoxic T lymphocyte (CTL) activity in mice, and NK activity of human lymphocytes in vitro. We found that DIMP and DEMP significantly inhibited NK and CTL activity in a dose-dependent manner. The inhibition induced by DIMP was stronger than that by DEMP. The effect of DIMP and DEMP on the splenic NK activity of mice was stronger than on the splenic CTL activity, and the human lymphocytes is more sensitive to DIMP and DEMP than the splenocytes of mice.

[The effects of transcutaneous electrical stimulation during sleep on obstructive sleep apnea]

OBJECTIVE

To study the effects of transcutaneous electrical stimulation during sleep on obstructive sleep apnea syndrom (OSAS).

METHOD

Sixteen patients with OSAS were studied by polysomnography during all-night sleep with and without submental transcutaneous electrical stimulation (TES) of the genioglossus.

RESULT

Fourteen of the 16 patients (87%) who accepted the TES were treated successfully (reduction of Al > 50%). The average apnea index showed a decrease of 29 events per hour when the TES were performed (P < 0.001). The average apnea time decreased from 22 to 7 sec (P < 0.001). The apnea time/TST decreased from 27% +/- 11% to 7% +/- 3%. The lowest SaO2 increased from 71% to 87% (P < 0.001). TES did not cause arousal. The sleep stages of SWS, and REM sleep effect (SE) increased significantly.

CONCLUSION

TES is a conservative but effective treatment in patients with obstructive sleep apnea syndrome, although it failed to improve central sleep apnea.

[Protective effects of methanolic extract of Oenanthe stolonifera (Roxb.) Wall. ex DC. on myocardial injury induced by ischemia and reperfusion in rats]

The methanolic extract Oenanthe stoloni fera iv, pretreatment can significantly prevent the arrhythmias induced by myocardial ischemia and reduce the myocardial infarct size in rats. It can also markedly prevent myocardial ischemia and reperfusion-induced arrhythmias. In addition, the methanolic extract of Oenanthe stoloni fera (100 mg/kg i.v.) helps significantly to decrease the MDA content and preserve the SOD activity in plasma.