An assessment of how the anterior cerebral artery anatomy impacts ACoA aneurysm formation based on CFD analysis

OBJECTIVE

The aim of this study was to identify independent anatomic, morphologic and hemodynamic features of the ACoA (anterior communicating artery) complex that serve as risk factors for the occurrence of ACoA aneurysms.

METHODS

Fifteen consecutive patients with 15 ACoA aneurysms were included. Computational fluid dynamics (CFD) simulations based on patient-specific models were carried out using 3D time-of-flight magnetic resonance angiography (3D-TOF-MRA) images. A reverse reconstruction technique was used to generate a pre-aneurysm vessel anatomy. Geometric parameters and hemodynamic changes were compared and evaluated.

RESULTS

The overall prevalence of symmetric, dysplastic, and absent A1 segments were 53.3%, 26.7%, and 20%. The mean wall shear stress (WSS) of the absent group (AG) was significantly higher than that of the symmetric group (SG) and dysplastic group (DG). The absolute mean A1 artery flow rate (410.2 ± 88 versus 439.4 ± 101 mL/min; p = .45) of the aneurysm side was similar between the SG and DG but significantly higher in the AG (528.1 ± 77 mL/min; p < .05). The A1-A2 angles of the aneurysm side showed no significant differences among the 3 groups (p = .32). However, the mean A1-A2 angle on the aneurysm side was smaller than the contralateral A1-A2 angle (101.9 ± 9.1˚ versus 120.3 ± 7.7˚; p <.05). A regression analysis demonstrated that high WSS was significantly associated with a large A1-A2 ratio (R2=0.52; p <.05).

CONCLUSIONS

ACoA aneurysms are a high-WSS pathology. Severe flow impingement and the anatomic vasculature structures play a role in triggering the occurrence of ACoA aneurysms.

Locating X-Ray Coronary Angiogram Keyframes via Long Short-Term Spatiotemporal Attention With Image-to-Patch Contrastive Learning

Locating the start, apex and end keyframes of moving contrast agents for keyframe counting in X-ray coronary angiography (XCA) is very important for the diagnosis and treatment of cardiovascular diseases. To locate these keyframes from the class-imbalanced and boundary-agnostic foreground vessel actions that overlap complex backgrounds, we propose long short-term spatiotemporal attention by integrating a convolutional long short-term memory (CLSTM) network into a multiscale Transformer to learn the segment- and sequence-level dependencies in the consecutive-frame-based deep features. Image-to-patch contrastive learning is further embedded between the CLSTM-based long-term spatiotemporal attention and Transformer-based short-term attention modules. The imagewise contrastive module reuses the long-term attention to contrast image-level foreground/background of XCA sequence, while patchwise contrastive projection selects the random patches of backgrounds as convolution kernels to project foreground/background frames into different latent spaces. A new XCA video dataset is collected to evaluate the proposed method. The experimental results show that the proposed method achieves a mAP (mean average precision) of 72.45% and a F-score of 0.8296, considerably outperforming the state-of-the-art methods. The source code is available at https://github.com/Binjie-Qin/STA-IPCon.

[Advances in the diagnosis, treatment, and prognosis of acute decompensatory cirrhosis]

Acute decompensatory cirrhosis is a common cause of hospital admission, readmission, and death, causing a heavy burden on patients, their families, and society. This article reviews the research advancement from the perspectives of concept evolution, pathogenesis, treatment, outcome, and prognosis models, providing new ideas for preventing and treating acute decompensatory cirrhosis.

Robust PCA Unrolling Network for Super-Resolution Vessel Extraction in X-Ray Coronary Angiography

Although robust PCA has been increasingly adopted to extract vessels from X-ray coronary angiography (XCA) images, challenging problems such as inefficient vessel-sparsity modelling, noisy and dynamic background artefacts, and high computational cost still remain unsolved. Therefore, we propose a novel robust PCA unrolling network with sparse feature selection for super-resolution XCA vessel imaging. Being embedded within a patch-wise spatiotemporal super-resolution framework that is built upon a pooling layer and a convolutional long short-term memory network, the proposed network can not only gradually prune complex vessel-like artefacts and noisy backgrounds in XCA during network training but also iteratively learn and select the high-level spatiotemporal semantic information of moving contrast agents flowing in the XCA-imaged vessels. The experimental results show that the proposed method significantly outperforms state-of-the-art methods, especially in the imaging of the vessel network and its distal vessels, by restoring the intensity and geometry profiles of heterogeneous vessels against complex and dynamic backgrounds. The source code is available at https://github.com/Binjie-Qin/RPCA-UNet.

[Research progress of sodium butyrate in metabolic-associated fatty liver disease]

Metabolic-associated fatty liver disease (MAFLD) has become the most common chronic liver disease affecting global public health, and its incidence rate is increasing year by year. The molecular mechanism of its pathogenesis is not yet fully understood, and there is a shortage of effective clinical prevention and treatment methods. Studies have found that sodium butyrate can participate in gene regulation, immune regulation, intestinal barrier function regulation, oxidative stress and other in-vivo physiological activities. Furthermore, it also plays an important role in preventing and alleviating the MAFLD occurrence and development. This article reviews the related studies of sodium butyrate on gene expression regulation, fat metabolism improvement, intestinal flora regulation, and steatohepatitis improvement with MAFLD.

Growth differentiation factor 11 relieves acute lung injury in mice by inhibiting inflammation and apoptosis

OBJECTIVE

Acute lung injury (ALI) is the most common organ damage in sepsis and sepsis-induced ALI is a clinically extremely dangerous disease. Therefore, it is essential to find an effective way to treat ALI. We hope to provide a new target for the treatment of clinical ALI by studying the effect of GDF11 on LPS-induced ALI.

MATERIALS AND METHODS

C57BL/6 male mice and lipopolysaccharide (LPS) were used to induce mouse ALI. Recombinant GDF11 protein was used to treat mice to detect the effect of GDF11 on mouse ALI. In addition, BEAS-2B cells were used to further validate the effects of GDF11 on inflammation and apoptosis of alveolar epithelial cells.

RESULTS

Recombinant GDF11 protein significantly reduced the expression of inflammatory factors and apoptosis-related pathways in mouse lung tissues. Overexpression of GDF11 in BEAS-2B cells also significantly attenuated the levels of inflammation and apoptosis in the cells. In addition, GDF11 can reduce the activity of TLR2/HMGB1/NF-κB signaling pathway, which is an important mechanism for GDF11 to play a role in lung protection.

CONCLUSIONS

GDF11 can exert lung protection effects by inhibiting the TLR2/HMGB1/NF-κB signaling pathway and reduce the level of inflammation and apoptosis of the lung.

Multilevel Risk Factors for Weight Change after Breast Cancer Diagnosis Among Black Women

Background: Weight gain after breast cancer diagnosis increases the risk of mortality. African American/Black breast cancer survivors are more likely to have excess body weight than their White counterparts, which may contribute to their higher mortality rate. Emerging evidence suggests that post-diagnosis weight gain may result from multilevel determinants. However, no study has investigated the multilevel characteristics among Black breast cancer survivors. Objective: To evaluate associations between individual-level factors and neighborhood social and built environment factors with weight change after breast cancer diagnosis among Black women. Methods: We evaluated associations of interest among 785 women enrolled in the Women's Circle of Health Follow-Up Study (WCHFS), a longitudinal study of Black breast cancer survivors in New Jersey. Weight change was primarily based on measurements at baseline and follow-up visits (Median: 10.3 and 23.2 mo. since diagnosis, respectively). Participants were grouped into categories of stable weight (52.4%), ≥3% weight loss (20.0%), and ≥3% weight gain (27.6%). Using multivariate- adjusted multinomial logistic regression and multilevel multinomial logistic regression, we evaluated relative risk ratios (RRRs) for associations between multilevel factors and post-diagnosis weight change category. Results: Black breast cancer survivors who were older at diagnosis, had higher household income, post-menopausal status, and higher baseline BMI were less likely to gain weight compared to women with stable weight. Former smoking, higher tumor stage, and chemotherapy were associated with increased relative risk of weight gain (e.g. RRR-chemo: 1.45, 95% CI: 1.01, 2.08). Black women residing in neighborhoods in the highest tertile for density of walkable destinations had a decreased relative risk of post- diagnosis weight gain (e.g. RRR-T3 highest density vs. T1 lowest: 0.39, 95% CI: 0.20, 0.75), while those residing in neighborhoods with higher density of fast food restaurants had increased relative risk of weight gain (RRR-T3 highest density vs. T1 lowest: 1.94, 95% CI: 1.23, 3.05). Conclusion: Both individual and neighborhood factors may influence the risk of weight gain among Black women after breast cancer diagnosis.

Voxel-wise meta-analysis of structural changes in gray matter of Parkinson's disease patients with mild cognitive impairment

Evidence from previous voxel-based morphometry (VBM) studies indicates that widespread brain regions are involved in Parkinson’s disease with mild cognitive impairment (PD-MCI). However, the spatial localization reported for gray matter (GM) abnormalities is heterogeneous. The aim of the present study was to quantitatively integrate studies on GM abnormalities observed in PD-MCI in order to determine whether a pattern exists. Eligible whole-brain VBM studies were identified by a systematic search of articles in PubMed and EMBASE databases spanning from 1995 to January 1, 2019. A meta-analysis was performed to investigate regional GM abnormalities in PD-MCI. The anisotropic effect size version of seed-based d mapping (AES-SDM) meta-analysis was conducted to explore the GMV differences of PD-MCI compared with PD patients with normal cognitive function (PD-NC). A total of 12 studies comprising 243 PD-MCI patients and 326 PD-NC were included in the meta-analysis. PD-MCI patients showed a robust GM decrease in the left insula and left superior temporal gyrus. Moreover, meta-regression analysis demonstrated that age, PD duration and stage, and Unified Parkinson’s Disease Rating Scale III and Mini-Mental State Examination scores might be partly correlated with the GM abnormalities observed in PD-MCI patients. The convergent findings of this quantitative meta-analysis revealed a characteristic neuroanatomical pattern in PD-MCI. The findings provide some evidence that MCI in PD may result in the breakdown of the insula and temporal gyrus, which may serve as specific regions of interest for further investigations.

Sequential vessel segmentation via deep channel attention network

Accurately segmenting contrast-filled vessels from X-ray coronary angiography (XCA) image sequence is an essential step for the diagnosis and therapy of coronary artery disease. However, developing automatic vessel segmentation is particularly challenging due to the overlapping structures, low contrast and the presence of complex and dynamic background artifacts in XCA images. This paper develops a novel encoder-decoder deep network architecture which exploits the several contextual frames of 2D+t sequential images in a sliding window centered at current frame to segment 2D vessel masks from the current frame. The architecture is equipped with temporal-spatial feature extraction in encoder stage, feature fusion in skip connection layers and channel attention mechanism in decoder stage. In the encoder stage, a series of 3D convolutional layers are employed to hierarchically extract temporal-spatial features. Skip connection layers subsequently fuse the temporal-spatial feature maps and deliver them to the corresponding decoder stages. To efficiently discriminate vessel features from the complex and noisy backgrounds in the XCA images, the decoder stage effectively utilizes channel attention blocks to refine the intermediate feature maps from skip connection layers for subsequently decoding the refined features in 2D ways to produce the segmented vessel masks. Furthermore, Dice loss function is implemented to train the proposed deep network in order to tackle the class imbalance problem in the XCA data due to the wide distribution of complex background artifacts. Extensive experiments by comparing our method with other state-of-the-art algorithms demonstrate the proposed method's superior performance over other methods in terms of the quantitative metrics and visual validation. To facilitate the reproductive research in XCA community, we publicly release our dataset and source codes at https://github.com/Binjie-Qin/SVS-net.

[Deformable Registration Network Reinforced by Joint Saliency Map]

Image outliers such as missing correspondences and large local deformations break the one-to-one pixelwise mapping between target image and moving image to be registered. Both traditional registration methods and deep-learning based deformable image registration methods fail to tackle this problem. This paper proposed an unsupervised globalto-local deformable registration network reinforced by joint saliency map to accurately, robustly and fast address the problem. The global-to-local network divided the overall learning of a complex mapping of image registration into a simpler global mapping learning and local residual mapping. The joint saliency map of the two images to be registered bidirectionally reinforced the whole network's forward estimation and back-propagation with uncertainty modeling and context-aware intelligence. The experimental results confirm the proposed method's performance advantages over the state-of-the-arts registration methods in the challenges image registration with missing correspondences and large local deformations.

Overexpression of miR-638 attenuated the effects of hypoxia/reoxygenation treatment on cell viability, cell apoptosis and autophagy by targeting ATG5 in the human cardiomyocytes

OBJECTIVE

Myocardial ischemia/reperfusion (I/R) injury largely contributed to the damage of myocardial tissues in patients with coronary disease, which may subsequently lead to heart failure. MicroRNAs (miRNAs) are considered to be involved in the process of myocardial I/R injury. The present study aimed to investigate the in vitro functional role of miR-638 in the myocardial I/R injury in the human cardiomyocytes (HCMs).

PATIENTS AND METHODS

MTT assay and flow cytometry assay were performed to determine cell viability and apoptosis of HCMs. Real Time-quantitative Polymerase Chain Reaction was used to determine miRNA and mRNA expression levels. The protein levels were determined by Western blot assay.

RESULTS

Hypoxia/reoxygenation (H/R) treatment suppressed cell viability, increased cell apoptotic rate and suppressed miR-638 expression in the HCMs. The downregulation of miR-638 suppressed cell viability and induced cell apoptosis in the HCMs. The overexpression of miR-638 attenuated the effects of H/R treatment on the cell viability and cell apoptosis in the HCMs. In addition, miR-638 suppressed the expression of autophagy-related 5 (ATG5) by targeting the 3'untranslated region of ATG5. Enforced expression of ATG5 reversed the effects of miR-638 overexpression on cell viability and cell apoptosis in H/R-treated HCMs. More importantly, H/R treatment promoted autophagy in the HCMs, and this effect was significantly reversed by miR-638 mimic transfection.

CONCLUSIONS

Our results suggested that the overexpression of miR-638 attenuated the effects of H/R treatment on cell viability, cell apoptosis and autophagy, at least partly by regulating the ATG5 expression in the HCMs.

Phase asymmetry ultrasound despeckling with fractional anisotropic diffusion and total variation

We propose an ultrasound speckle filtering method for not only preserving various edge features but also filtering tissue-dependent complex speckle noises in ultrasound images. The key idea is to detect these various edges using a phase congruence-based edge significance measure called phase asymmetry (PAS), which is invariant to the intensity amplitude of edges and takes 0 in non-edge smooth regions and 1 at the idea step edge, while also taking intermediate values at slowly varying ramp edges. By leveraging the PAS metric in designing weighting coefficients to maintain a balance between fractional-order anisotropic diffusion and total variation (TV) filters in TV cost function, we propose a new fractional TV framework to not only achieve the best despeckling performance with ramp edge preservation but also reduce the staircase effect produced by integral-order filters. Then, we exploit the PAS metric in designing a new fractional-order diffusion coefficient to properly preserve low-contrast edges in diffusion filtering. Finally, different from fixed fractional-order diffusion filters, an adaptive fractional order is introduced based on the PAS metric to enhance various weak edges in the spatially transitional areas between objects. The proposed fractional TV model is minimized using the gradient descent method to obtain the final denoised image. The experimental results and real application of ultrasound breast image segmentation show that the proposed method outperforms other state-of-the-art ultrasound despeckling filters for both speckle reduction and feature preservation in terms of visual evaluation and quantitative indices. The best scores on feature similarity indices have achieved 0.867, 0.844 and 0.834 under three different levels of noise, while the best breast ultrasound segmentation accuracy in terms of the mean and median dice similarity coefficient are 96.25% and 96.15%, respectively.

Texture Variation Adaptive Image Denoising With Nonlocal PCA

Image textures, as a kind of local variations, provide important information for the human visual system. Many image textures, especially the small-scale or stochastic textures, are rich in high-frequency variations, and are difficult to be preserved. Current state-of-the-art denoising algorithms typically adopt a nonlocal approach consisting of image patch grouping and group-wise denoising filtering. To achieve a better image denoising while preserving the variations in texture, we first adaptively group high correlated image patches with the same kinds of texture elements (texels) via an adaptive clustering method. This adaptive clustering method is applied in an over-clustering-and-iterative-merging approach, where its noise robustness is improved with a custom merging threshold relating to the noise level and cluster size. For texture-preserving denoising of each cluster, considering that the variations in texture are captured and wrapped in not only the between-dimension energy variations but also the within-dimension variations of PCA transform coefficients, we further propose a PCA-transform-domain variation adaptive filtering method to preserve the local variations in textures. Experiments on natural images show the superiority of the proposed transform-domain variation adaptive filtering to traditional PCA-based hard or soft threshold filtering. As a whole, the proposed denoising method achieves a favorable texture-preserving performance both quantitatively and visually, especially for irregular textures, which is further verified in camera raw image denoising.

Multi-Channel and Multi-Model-Based Autoencoding Prior for Grayscale Image Restoration

Image restoration (IR) is a long-standing challenging problem in low-level image processing. It is of utmost importance to learn good image priors for pursuing visually pleasing results. In this paper, we develop a multi-channel and multi-model-based denoising autoencoder network as image prior for solving IR problem. Specifically, the network that trained on RGB-channel images is used to construct a prior at first, and then the learned prior is incorporated into single-channel grayscale IR tasks. To achieve the goal, we employ the auxiliary variable technique to integrate the higher-dimensional network-driven prior information into the iterative restoration procedure. In addition, according to the weighted aggregation idea, a multi-model strategy is put forward to enhance the network stability that favors to avoid getting trapped in local optima. Extensive experiments on image deblurring and deblocking tasks show that the proposed algorithm is efficient, robust, and yields state-of-the-art restoration quality on grayscale images.

The relationship between plasma homocysteine levels and MTHFR gene variation, age, and sex in Northeast China

Background

Hyperhomocysteinemia (HHcy) is the risk factor for cardiovascular disease and stroke. However, the impacts on the genetic variation of methylene tetrahydrofolate reductase (MTHFR) on plasma homocysteine levels in the Northeast Chinese population have not been studied. Therefore, this study was carried out to determine the relationship between HHcy and MTHFR gene variation, and whether it was influenced by age and sex of the population in Northeast China.

Materials and Methods

A total of 466 subjects were randomly enrolled in this study. According to the homocysteine levels (Hcy ≥ 15 μmol/L) of the subjects, they were divided into hyperhomocysteine (HHcy = 206) and normal homocysteine (Hcy = 260). Polymerase chain reaction/high-resolution dissolution curve and homocysteine determination kit methods were used for genotype testing and homocysteine detection, respectively.

Results

High plasma homocysteine levels are associated with MTHFR 677T and 1298A [P < 0.00, odds ratio (confidence interval) = 1.842 (1.418-2.394) >1], which is related to increasing age (P_range = 0.0005-0.0161), with the homocysteine levels of males higher than females (P < 0.0001).

Conclusion

High plasma homocysteine levels were linked to the MTHFR gene mutation. In addition, plasma homocysteine levels increased significantly with age with male's homocysteine levels higher than that of females.

Accurate vessel extraction via tensor completion of background layer in X-ray coronary angiograms

This paper proposes an effective method for accurately recovering vessel structures and intensity information from the X-ray coronary angiography (XCA) images of moving organs or tissues. Specifically, a global logarithm transformation of XCA images is implemented to fit the X-ray attenuation sum model of vessel/background layers into a low-rank, sparse decomposition model for vessel/background separation. The contrast-filled vessel structures are extracted by distinguishing the vessels from the low-rank backgrounds by using a robust principal component analysis and by constructing a vessel mask via Radon-like feature filtering plus spatially adaptive thresholding. Subsequently, the low-rankness and inter-frame spatio-temporal connectivity in the complex and noisy backgrounds are used to recover the vessel-masked background regions using tensor completion of all other background regions, while the twist tensor nuclear norm is minimized to complete the background layers. Finally, the method is able to accurately extract vessels' intensities from the noisy XCA data by subtracting the completed background layers from the overall XCA images. We evaluated the vessel visibility of resulting images on real X-ray angiography data and evaluated the accuracy of vessel intensity recovery on synthetic data. Experiment results show the superiority of the proposed method over the state-of-the-art methods.

[Analysis of correlation between serum fatty acid profile and cognitive impairment in the elderly]

Objective: To explore the relationship between cognitive impairment and serum fatty acid profile. Methods: Participants aged ≥60 years were selected from 3 communities in Shijiazhuang in 2015. The questionnaire was performed to collect basic information. And Montreal Cognitive Assessment was applied for the evaluation of cognitive impairment. Blood lipid parameters and serum fatty acid profiles were analyzed for all the subjects. A total of 529 subjects were finally included in this research. Multivariate ordinal logistic model was used to analyze the relationship between serum fatty acid profile and cognitive impairment. Results: Normal, mild and moderate cognitive impairment accounted for 41.2% (n=218), 51.4% (n=272) and 7.4% (n=39) of all the subjects respectively. With control of age, gender, education, total cholesterol (TC), total triglyceride (TG), low density lipoprotein cholesterol (LDL-C), and high density lipoprotein cholesterol (HDL-C), the OR (95%CI) of eicosenoic acid, nervonic acid and ratio of n-3 and n-6 polyunsaturated fatty acid (n-3/n-6) was 1.06 (1.01-1.10), 0.93 (0.91-0.96), and 0.17 (0.04-0.73). Conclusion: The risk of cognitive impairment decreased with the raise of serum nervonic acid concentration and n-3/n-6, and increased with the raise of serum eicosenoic acid concentration.

[The diagnostic framework for screening Alzheimer's disease in the Chinese population]

Criteria for diagnosis of Alzheimer's disease (AD) is not available in China. The international criteria is not a proper choice due to issues such as translation and lead to low diagnostic rate and high rate of missed diagnosis. The research group of Alzheimer's Disease Chinese (ADC) reviewed knowledge and techniques in neuropsychology, neuroimaging, molecular biology, and clinical neurology, and systematically studied the detection techniques such as memory, language, visuospatial, executive function, and medial temporal lobe visual scores on MRI, and their optimal threshold and diagnostic value for the diagnosis of AD. Through a systematic review and consensus meeting, a diagnostic framework for screening AD in the Chinese population was established. Among these methods, an operational standard for clinical pathology models increased the diagnostic sensitivity by 15%. The sensitivity and specificity of screening memory impairment increased by 18.1% and 11.6%, respectively. The sensitivity of screening medial temporal lobe atrophy increased by 24.5% and missed diagnosis was decreased by 34.5%. An operational standard for clinical biology models, incorporating the latest molecular imaging and molecular biology techniques, has enabled the early diagnosis of AD in China. The framework combines a principled diagnostic guideline with an operational screening protocol, which is applicable to all clinical settings and of great significance for the early detection, early diagnosis and early treatment of AD.

[Dementia screening and diagnostic framework in Chinese population]

There are no standard diagnostic criteria for Alzheimer's disease (AD) in China. The copied international criteria has led to a high rate of missed diagnosis due to issues such as translation and cultural discrepancy. Under the principles of semantic equivalence, content equivalence and performance equivalence, the research group of Alzheimer's Disease Chinese (ADC) adopted several effective methods, such as two-way translation, content conversion, performance evaluation, etc. to systematically study the cognitive, behavioral, functional, and general assessment techniques in dementia screening and diagnosis, as well as their screening thresholds and diagnostic values. We also established a dementia screening and assessment framework in clinical practice through systematic reviews and group consensus. It has improved the early diagnosis rate of dementia in China, been accepted by home and abroad academic institutions, which is of great significance for early diagnosis and treatment of dementia.

Efficacy, acceptability, and tolerability of antidepressant treatments for patients with post-stroke depression: a network meta-analysis

The aim of this study was to investigate the efficacy, acceptability, and tolerability of antidepressants in treating post-stroke depression (PSD) by performing a network meta-analysis of randomized controlled trials of the current literature. Eligible studies were retrieved from online databases, and relevant data were extracted. The primary outcome was efficacy as measured by the mean change in overall depressive symptoms. Secondary outcomes included discontinued treatment for any reason and specifically due to adverse events. Fourteen trials were eligible, which included 949 participants and 9 antidepressant treatments. Few significant differences were found for all outcomes. For the primary outcome, doxepin, paroxetine, and nortriptyline were significantly more effective than a placebo [standardized mean differences: −1.93 (95%CI=−3.56 to −0.29), −1.39 (95%CI=−2.59 to −0.21), and −1.25 (95%CI=−2.46 to −0.04), respectively]. Insufficient evidence exists to select a preferred antidepressant for treating patients with post-stroke depression, and our study provides little evidence that paroxetine may be the potential choice when starting treatment for PSD. Future studies with paroxetine and larger sample sizes, multiple medical centers, and sufficient intervention durations is needed for improving the current evidence.

Non-alcoholic fatty liver disease is associated with stroke severity and progression of brainstem infarctions

BACKGROUND AND PURPOSE

Non-alcoholic fatty liver disease (NAFLD) is closely correlated to visceral obesity, dyslipidaemia, insulin resistance and type 2 diabetes mellitus. We sought to assess the association between a specific stroke subgroup, brainstem infarctions (BSIs) and NAFLD. Furthermore, we evaluated whether NAFLD is an independent risk factor in patients with BSIs.

METHODS

Non-alcoholic fatty liver disease was assessed in 306 patients with radiologically confirmed BSIs via liver ultrasound. Differences between patients with and without NAFLD were compared. Data associated with stroke severity and progression after admission were collected.

RESULTS

Non-alcoholic fatty liver disease was found in 130 (42.5%) patients with acute BSIs; 58 (19.0%) had National Institutes of Health Stroke Scale scores >7 and 57 (18.6%) had progression after admission. Initial National Institutes of Health Stroke Scale scores, incidence of progression and stroke severity, and modified Rankin Scale scores at discharge were significantly higher in patients with NAFLD than in those without NAFLD. NAFLD was associated with stroke severity [Cox regression: hazard ratio (HR), 2.243; 95% confidence interval (CI), 1.254-4.013, P < 0.01]. This risk remained statistically significant after controlling for age, gender, diabetes mellitus and C-reactive protein (HR, 2.327; 95% CI, 1.252-4.324, P < 0.01). In addition, NAFLD was associated with progression (HR, 2.155; 95% CI, 1.201-3.865, P < 0.05) and remained significant after controlling for age, gender, diabetes mellitus, fibrinogen and C-reactive protein (HR, 2.378; 95% CI, 1.260-4.486, P < 0.01).

CONCLUSIONS

These results suggest that NAFLD is a potential risk factor when evaluating the severity and progression of acute BSIs. This relationship is independent of classic risk factors and metabolic syndrome features.

Ultrasound Imaging Technologies for Breast Cancer Detection and Management: A Review

Ultrasound imaging is a commonly used modality for breast cancer detection and diagnosis. In this review, we summarize ultrasound imaging technologies and their clinical applications for the management of breast cancer patients. The technologies include ultrasound elastography, contrast-enhanced ultrasound, 3-D ultrasound, automatic breast ultrasound and computer-aided detection of breast ultrasound. We summarize the study results seen in the literature and discuss their future directions. We also provide a review of ultrasound-guided, breast biopsy and the fusion of ultrasound with other imaging modalities, especially magnetic resonance imaging (MRI). For comparison, we also discuss the diagnostic performance of mammography, MRI, positron emission tomography and computed tomography for breast cancer diagnosis at the end of this review. New ultrasound imaging techniques, ultrasound-guided biopsy and the fusion of ultrasound with other modalities provide important tools for the management of breast patients.

A singular K-space model for fast reconstruction of magnetic resonance images from undersampled data

Reconstructing magnetic resonance images from undersampled k-space data is a challenging problem. This paper introduces a novel method of image reconstruction from undersampled k-space data based on the concept of singularizing operators and a novel singular k-space model. Exploring the sparsity of an image in the k-space, the singular k-space model (SKM) is proposed in terms of the k-space functions of a singularizing operator. The singularizing operator is constructed by combining basic difference operators. An algorithm is developed to reliably estimate the model parameters from undersampled k-space data. The estimated parameters are then used to recover the missing k-space data through the model, subsequently achieving high-quality reconstruction of the image using inverse Fourier transform. Experiments on physical phantom and real brain MR images have shown that the proposed SKM method constantly outperforms the popular total variation (TV) and the classical zero-filling (ZF) methods regardless of the undersampling rates, the noise levels, and the image structures. For the same objective quality of the reconstructed images, the proposed method requires much less k-space data than the TV method. The SKM method is an effective method for fast MRI reconstruction from the undersampled k-space data. Graphical abstract Two Real Images and their sparsified images by singularizing operator.

[Epidemiological survey of visual impairment in Funing County, Jiangsu]

Objective: To investigate the prevalence of visual impairment and factors associated with visual impairment among people aged 50 years and above in Funing County, Jiangsu Province. Methods: Cross-sectional study. Random cluster sampling was used in selecting individuals aged ≥50 years in 30 clusters, and 5 947 individuals received visual acuity testing and eye examination. Stata 13.0 software was used to analyze the data. Multivariate logistic regression was used to detect possible factors of visual impairment such as age, gender and education. Statistical significance was defined as P< 0.05. Results: A total of 6 145 persons aged 50 years and above were enumerated, and 5 947 (96.8%) participants were examined. Based on the criteria of World Health Organization (WHO) visual impairment classification and presenting visual acuity, 138 persons were diagnosed as blindness, and 1 405 persons were diagnosed as low vision. The prevalence of blindness and low vision was 2.32% and 23.63%, respectively. And the prevalence of visual impairment was 25.95%. Based on the criteria of WHO visual impairment classification and best-corrected visual acuity, 92 persons were diagnosed as blindness, and 383 persons were diagnosed as low vision. The prevalence of blindness and low vision was 1.55% and 6.44%, respectively. And the prevalence of visual impairment was 7.99%. Concerning presenting visual acuity and best-corrected visual acuity, the prevalence of blindness and low vision was higher in old people, females and less educated persons. Cataract (46.63%) was the leading cause of blindness. Uncorrected refractive error (36.51%) was also a main cause of visual impairment. Conclusion: The prevalence of visual impairment is higher in old people, females and less educated persons in Funing County, Jiangsu Province. Cataract is still the leading cause of visual impairment. (Chin J Ophthalmol, 2017, 53: 502-508).

Fast single image super-resolution using estimated low-frequency k-space data in MRI

PURPOSE

Single image super-resolution (SR) is highly desired in many fields but obtaining it is often technically limited in practice. The purpose of this study was to propose a simple, rapid and robust single image SR method in magnetic resonance (MR) imaging (MRI).

METHODS

The idea is based on the mathematical formulation of the intrinsic link in k-space between a given (modulus) low-resolution (LR) image and the desired SR image. The method consists of two steps: 1) estimating the low-frequency k-space data of the desired SR image from a single LR image; 2) reconstructing the SR image using the estimated low-frequency and zero-filled high-frequency k-space data. The method was evaluated on digital phantom images, physical phantom MR images and real brain MR images, and compared with existing SR methods.

RESULTS

The proposed SR method exhibited a good robustness by reaching a clearly higher PSNR (25.77dB) and SSIM (0.991) averaged over different noise levels in comparison with existing edge-guided nonlinear interpolation (EGNI) (PSNR=23.78dB, SSIM=0.983), zero-filling (ZF) (PSNR=24.09dB, SSIM=0.985) and total variation (TV) (PSNR=24.54dB, SSIM=0.987) methods while presenting the same order of computation time as the ZF method but being much faster than the EGNI or TV method. The average PSNR or SSIM over different slice images of the proposed method (PSNR=26.33 dB or SSIM=0.955) was also higher than the EGNI (PSNR=25.07dB or SSIM=0.952), ZF (PSNR=24.97dB or SSIM=0.950) and TV (PSNR=25.70dB or SSIM=0.953) methods, demonstrating its good robustness to variation in anatomical structure of the images. Meanwhile, the proposed method always produced less ringing artifacts than the ZF method, gave a clearer image than the EGNI method, and did not exhibit any blocking effect presented in the TV method. In addition, the proposed method yielded the highest spatial consistency in the inter-slice dimension among the four methods.

CONCLUSIONS

This study proposed a fast, robust and efficient single image SR method with high spatial consistency in the inter-slice dimension for clinical MR images by estimating the low-frequency k-space data of the desired SR image from a single spatial modulus LR image.

Parasites, nutrition, immune responses and biology of metabolic tissues

Nutritional immunology, immunometabolism and identification of novel immunotherapeutic targets are areas of active investigation in parasitology. There is a well-documented crosstalk among immune cells and cells in metabolically active tissues that is important for homeostasis. The numbers and function of these cells are altered by obesity leading to inflammation. A variety of helminths spend some part of their life cycle in the gastrointestinal tract and even entirely enteral nematode infections exert beneficial effects on glucose and lipid metabolism. The foundation of this review is the ability of enteric nematode infections to improve obesity-induced type 2 diabetes and the metabolic syndrome, which are significant health issues in developed areas. It considers the impact of nutrition and specific nutritional deficiencies, which are occur in both undeveloped and developed areas, on the host's ability mount a protective immune response against parasitic nematodes. There are a number of proposed mechanisms by which parasitic nematodes can impact metabolism including effects gastrointestinal hormones, altering epithelial function and changing the number and/or phenotype of immune cells in metabolic tissues. Nematodes can also exert their beneficial effects through Th2 cytokines that activate the transcription factor STAT6, which upregulates genes that regulate glucose and lipid metabolism.

Parenting styles and body mass index: a systematic review of prospective studies among children

BACKGROUND

Parenting style may be an important determinant of an individual's future weight status. However, reviews that evaluate the relationship between parenting style and weight-related outcomes have not focused on prospective studies.

METHODS

We systematically searched PubMed, Embase and PsychInfo for studies published between 1995 and 2016 that evaluated the prospective relationship between parenting style experienced in childhood and subsequent weight outcomes.

RESULTS

We identified 11 prospective cohort studies. Among the eight studies that categorized parenting style into distinct groups (i.e. authoritative, authoritarian, permissive and neglectful), five provided evidence that authoritative parenting was associated with lower body mass index gains. Among the six highest quality studies, four suggested a protective role of authoritative parenting style against adverse weight-related outcomes. However, only one study controlled for a comprehensive set of confounders, and the small number of studies conducted within certain age groups precluded our ability to ascertain critical periods when parenting style is most strongly related to child weight.

CONCLUSIONS

The present literature supports the idea that authoritative parenting may be protective against later overweight and obesity, although findings are mixed. More prospective cohort studies of longer durations, with more sophisticated methods that examine age-varying relationships, and that control for a comprehensive set of confounders, are needed.

Randomized controlled trials of serotonin-norepinephrine reuptake inhibitor in treating major depressive disorder in children and adolescents: a meta-analysis of efficacy and acceptability

New generation antidepressant therapies, including serotonin-norepinephrine reuptake inhibitor (SNRIs), were introduced in the late 1980s; however, few comprehensive studies have compared the benefits and risks of various contemporary treatments for major depressive disorder (MDD) in young patients. A comprehensive literature search of PubMed, Cochrane, Embase, Web of Science, and PsycINFO databases was conducted from 1970 to January 2015. Only clinical trials that randomly assigned one SNRI or placebo to patients aged 7 to 18 years who met the diagnostic criteria for major depressive disorder were included. Treatment success, dropout rate, and suicidal ideation/attempt outcomes were measured. Primary efficacy was determined by pooling the risk ratios (RRs) of treatment response and remission. Acceptability was determined by pooling the RRs of dropouts for all reasons and for adverse effects as well as suicide-risk outcomes. Five trials with a total of 973 patients were included. SNRIs were not significantly more effective than placebo for treatment response but were for remission. The comparison of patients taking SNRIs that dropped out for all reasons and those taking placebo did not reach statistical significance. Significantly more patients taking SNRIs dropped out for adverse effects than those taking placebo. No significant difference was found in suicide-related risk outcomes. SNRI therapy does not display a superior efficacy and is not better tolerated compared to placebo in these young patients. However, duloxetine has a potential beneficial effect for depression in young populations, showing a need for further research.

[Poisson Noise Removal Using Patch-order Resampling PCA Algorithm]

The problem of Poisson denoising is common in various photon-limited imaging applications, especialy in low-light imaging, astronomy and nuclear medical applications. Due to the smal sample problem and the related insufficient self-similarity between patches of whole image, many denoising algorithms cannot obtain the favorable denoising performance. We propose patch-order resampling PCA algorithm for Poisson noise reduction. Firstly, we use the patch-ordered operations to sort the extracted image patches and exploit the bootstrap resampling method to resample the different blocks of spectral images to obtain more data matrix of image samples. Then, we select the patches with largest weights corresponding to the vectors of image samples data matrix as the most similar patches. Finaly, we use principal component analysis algorithm for processing the image to obtain the final denoised image. Experiments results show that the proposed method achieves excelent Poisson noise removal performance in the photon-limited images with smal sample problems.

Abstract P3-07-51: Regulation of DNA methyltransferases via TRAF6 determines breast cancer response to decitabine

Background: Tumorigenesis involves both genetic and epigenetic changes. Epigenetic alterations are reversible and are promising cancer therapeutic targets. Decitabine (5-aza-2'-deoxycytidine), a DNA methyltransferase inhibitor, is FDA approved for hematological malignancies. However, the effect of decitabine in breast cancer is not completely understood. Previous reports indicated that one decitabine mechanism involves regulation of protein levels for DNMT1, the major DNA methyltransferase that methylates hemimethylated CpG di-nucleotides in DNA. However, the E3 ligase involved in this process has not been identified. Whether decitabine also regulates DNMT3A and 3B in a similar fashion remains unclear. Therefore, our goals were to 1) understand mechanisms underlying decitabine action, 2) test the antitumor activity of decitabine in breast cancer models and 3) identify biomarkers associated with response to decitabine.

Methods and Results: Western blots of breast cancer cell lines showed that DNMT1, DNMT3A, and DNMT3B protein levels decreased following decitabine treatment without a reduction in mRNA levels. Bioinformatic analysis of DNA methyltransferase sequences revealed a potential TRAF6 binding motif, and the interaction with TRAF6 (TNF receptor-associated factor 6) was confirmed by IP. TRAF6 functions as an E3 ligase. To determine whether TRAF6 might be the E3 ligase responsible for the degradation of DNMTs after decitabine treatment, we knocked down TRAF6 by RNA interference or knocked out the TRAF6 gene by CRISPR/Cas9. Down regulation of TRAF6 attenuated DNMT ubiquitination and increased DNMT protein levels, suggesting that TRAF6 might mediate proteasome-dependent degradation of all three DNMTs. This was further confirmed by reconstituting the knockout cells with WT and a TRAF6-C70A mutant, followed by assessing DNMT protein levels. Global DNA methylation was also increased after TRAF6 depletion and was confirmed in TRAF6 knock out cells in which DNMT levels were unaffected by decitabine. Cell cytotoxicity and colony forming assays showed that TRAF6 knockout cells were resistant to decitabine, suggesting that a major decitabine mechanism of action is through the regulation of TRAF6 which, in turn, degrades DNMTs, leading to decreased global methylation. Finally, decitabine significantly induced TRAF6 at both mRNA and protein levels, a process that might create positive feedback leading to increased degradation of DNMT proteins upon decitabine treatment. Based on these results, we further hypothesized that levels of the three DNMTs might influence decitabine response. Using 18 breast cancer patient derived xenograft (PDX) models, we found a wide range of DNMT protein levels regardless of ER/HER2 status. DNMT levels in the PDX models were directly associated with sensitivity to decitabine treatment, confirming our hypothesis.

Conclusion: Our data showed that decitabine might be an effective agent for treating breast cancer and revealed a novel mechanism underlying decitabine treatment. Baseline DNMT protein levels may serve as a biomarker for predicting decitabine drug response.

Citation Format: Yu J, Qin B, Boughey JC, Moyer AM, Visscher DW, Sinnwell JP, Yin P, Thompson KJ, Docter TJ, Kalari KR, Suman VJ, Wieben ED, Felten SJ, Conners AL, Jones KN, McLaughlin SA, Copland JA III, Moreno Aspitia A, Northfelt DW, Gray RJ, Ingle JN, Lou Z, Weinshilboum R, Goetz MP, Wang L. Regulation of DNA methyltransferases via TRAF6 determines breast cancer response to decitabine. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-51.

Two-hierarchical nonnegative matrix factorization distinguishing the fluorescent targets from autofluorescence for fluorescence imaging

BACKGROUND

Nonnegative matrix factorization (NMF) has been used in blind fluorescence unmixing for multispectral in-vivo fluorescence imaging, which decomposes a mixed source data into a set of constituent fluorescence spectra and corresponding concentrations. However, most classical NMF algorithms have ill convergence problems and they always fail to unmix multiple fluorescent targets from background autofluorescence for the sparse acquisition of multispectral fluorescence imaging, which introduces incomplete measurements and severe discontinuities in multispectral fluorescence emissions across the multiple spectral bands.

METHODS

Observing the spatial distinction between the diffusive autofluorescence and the sparse fluorescent targets, we propose to separate the mixed sparse multispectral data into equality constrained two-hierarchical updating within NMF framework by dividing the concentration matrix of entire endmembers into two hierarchies: the fluorescence targets and the background autofluorescence. Specifically, when updating concentrations of multiple fluorescent targets in the two-hierarchical NMF, we assume that the concentration of autofluorescence is fixed and known, and vice versa. Furthermore, a sparsity constraint is imposed on the concentration matrix components of fluorescence targets only.

RESULTS

Synthetic data sets, in vivo fluorescence imaging data are employed to demonstrate and validate the performance of our approach. The proposed algorithm can achieve more satisfying results of spectral unmixing and autofluorescence removal compared to other state-of-the-art methods, especially for the sparse multispectral fluorescence imaging.

CONCLUSIONS

The proposed algorithm can successfully tackle the sparse acquisition and ill-posed problems in the NMF-based fluorescence unmixing through equality constraint along with partial sparsity constraint during two-hierarchical NMF optimization, at which fixing sparsity constrained target fluorescence can make the update of autofluorescence as accurate as possible and vice versa.

Flagellar kinematics and swimming of algal cells in viscoelastic fluids

The motility of microorganisms is influenced greatly by their hydrodynamic interactions with the fluidic environment they inhabit. We show by direct experimental observation of the bi-flagellated alga Chlamydomonas reinhardtii that fluid elasticity and viscosity strongly influence the beating pattern - the gait - and thereby control the propulsion speed. The beating frequency and the wave speed characterizing the cyclical bending are both enhanced by fluid elasticity. Despite these enhancements, the net swimming speed of the alga is hindered for fluids that are sufficiently elastic. The origin of this complex response lies in the interplay between the elasticity-induced changes in the spatial and temporal aspects of the flagellar cycle and the buildup and subsequent relaxation of elastic stresses during the power and recovery strokes.

Determining critical nutrient thresholds needed to control harmful cyanobacterial blooms in eutrophic Lake Taihu, China

Nutrient overenrichment has led to dramatic increases in harmful cyanobacterial blooms, creating serious threats to drinking water supplies, ecological and economic sustainability of freshwater ecosystems. Nutrient-cyanobacterial bloom interactions were examined in eutrophic Lake Taihu, China. In situ microcosm nutrient dilution bioassays and mesocosm nutrient addition experiments were conducted to determine nitrogen (N) and phosphorus (P) concentration and load thresholds needed to control cyanobacterial bloom formation. Blooms were dominated by toxic, non N2 fixing Microcystis spp, from May to December. Dilution bioassays showed seasonality in nutrient limitation, with P-availability controlling prebloom spring conditions and N-availability controlling summer-fall blooms. Nutrient dilution and enrichment bioassays indicated that total nitrogen (TN) and total phosphorus (TP) concentration thresholds should be targeted at below 0.80 mg L(–1) and 0.05 mg L(–1), respectively, to limit intrinsic growth rates of Microcystis dominated blooms. Based on estimates of nutrient loading and observed stoichiometry of phytoplankton biomass, 61–71% TN and 20–46% TP reduction are necessary to bring Taihu’s phytoplankton biomass to “acceptable” sub-bloom conditions of less than 20 μg L(–1) chlorophyll a.

Bilateral repetitive transcranial magnetic stimulation for treatment-resistant depression: a systematic review and meta-analysis of randomized controlled trials

There has been concern regarding the use of controversial paradigms for repetitive transcranial magnetic stimulation (rTMS) to manage treatment-resistant depression (TRD). This meta-analysis assessed the efficacy of bilateral rTMS compared with unilateral and sham rTMS in patients with TRD. PubMed, Embase, CENTRAL, PsycINFO, Web of Science, EAGLE and NTIS databases were searched to identify relevant studies, and randomized controlled trials (RCTs) on bilateral rTMS for TRD patients were included. The response was defined as the primary outcome, and remission was the secondary outcome. Ten RCTs that included 634 patients met the eligibility criteria. The risk ratio (RRs) of both the primary and secondary outcomes of bilateral rTMS showed non-significant increases compared to unilateral rTMS (RR=1.01, P=0.93; odds ratio [OR]=0.77, P=0.22). Notably, the RR of the primary bilateral rTMS outcome was significantly increased compared to that for sham rTMS (RR=3.43, P=0.0004). The results of our analysis demonstrated that bilateral rTMS was significantly more effective than sham rTMS but not unilateral rTMS in patients with TRD. Thus, bilateral rTMS may not be a useful paradigm for patients with TRD.