Assessment of intracranial aneurysm rupture risk using a point cloud-based deep learning model.

Background and Purpose: Precisely assessing the likelihood of an intracranial aneurysm rupturing is critical for guiding clinical decision-making. The objective of this study is to construct and validate a deep learning framework utilizing point clouds to forecast the likelihood of aneurysm rupturing. Methods: The dataset included in this study consisted of a total of 623 aneurysms, with 211 of them classified as ruptured and 412 as unruptured, which were obtained from two separate projects within the AneuX morphology database. The HUG project, which included 124 ruptured aneurysms and 340 unruptured aneurysms, was used to train and internally validate the model. For external validation, another project named @neurIST was used, which included 87 ruptured and 72 unruptured aneurysms. A standardized method was employed to isolate aneurysms and a segment of their parent vessels from the original 3D vessel models. These models were then converted into a point cloud format using open3d package to facilitate training of the deep learning network. The PointNet++ architecture was utilized to process the models and generate risk scores through a softmax layer. Finally, two models, the dome and cut1 model, were established and then subjected to a comprehensive comparison of statistical indices with the LASSO regression model built by the dataset authors. Results: The cut1 model outperformed the dome model in the 5-fold cross-validation, with the mean AUC values of 0.85 and 0.81, respectively. Furthermore, the cut1 model beat the morphology-based LASSO regression model with an AUC of 0.82. However, as the original dataset authors stated, we observed potential generalizability concerns when applying trained models to datasets with different selection biases. Nevertheless, our method outperformed the LASSO regression model in terms of generalizability, with an AUC of 0.71 versus 0.67. Conclusion: The point cloud, as a 3D visualization technique for intracranial aneurysms, can effectively capture the spatial contour and morphological aspects of aneurysms. More structural features between the aneurysm and its parent vessels can be exposed by keeping a portion of the parent vessels, enhancing the model's performance. The point cloud-based deep learning model exhibited good performance in predicting rupture risk while also facing challenges in generalizability.

Left main coronary artery morphological phenotypes and its hemodynamic properties.

BACKGROUND: Atherosclerosis may be linked to morphological defects that lead to variances in coronary artery hemodynamics. Few objective strategies exit at present for generalizing morphological phenotypes of coronary arteries in terms of hemodynamics. We used unsupervised clustering (UC) to classify the morphology of the left main coronary artery (LM) and looked at how hemodynamic distribution differed between phenotypes. METHODS: In this study, 76 LMs were obtained from 76 patients. After LMs were reconstructed with coronary computed tomography angiography, centerlines were used to extract the geometric characteristics. Unsupervised clustering was carried out using these characteristics to identify distinct morphological phenotypes of LMs. The time-averaged wall shear stress (TAWSS) for each phenotype was investigated by means of computational fluid dynamics (CFD) analysis of the left coronary artery. RESULTS: We identified four clusters (i.e., four phenotypes): Cluster 1 had a shorter stem and thinner branches (n = 26); Cluster 2 had a larger bifurcation angle (n = 10); Cluster 3 had an ostium at an angulation to the coronary sinus and a more curved stem, and thick branches (n = 10); and Cluster 4 had an ostium at an angulation to the coronary sinus and a flatter stem (n = 14). TAWSS features varied widely across phenotypes. Nodes with low TAWSS (L-TAWSS) were typically found around the branching points of the left anterior descending artery (LAD), particularly in Cluster 2. CONCLUSION: Our findings demonstrated that UC is a powerful technique for morphologically classifying LMs. Different LM phenotypes exhibited distinct hemodynamic characteristics in certain regions. This morphological clustering method could aid in identifying people at high risk for developing coronary atherosclerosis, hence facilitating early intervention.

The feasibility of early detecting coronary artery disease using deep learning-based algorithm based on electrocardiography.

BACKGROUND: Coronary Artery Disease (CAD) is a major cause of morbidity and mortality, yet it is frequently asymptomatic in the early stages and hence goes undetected. OBJECTIVE: We aimed to develop a novel artificial intelligence-based approach for early detection of CAD patients based solely on electrocardiogram (ECG). METHODS: This study included patients with suspected CAD who had standard 10-s resting 12-lead ECGs and coronary computed tomography angiography (cCTA) results within 4 weeks or less. The ECG and cCTA data from the same patient were matched based on their hospitalization or outpatient ID. All matched data pairs were then randomly divided into training, validation dataset for model development based on convolutional neural network (CNN) and test dataset for model evaluation. The accuracy (Acc), specificity (Spec), sensitivity (Sen), positive predictive value (PPV), negative predictive value (NPV) and area under the receiver operating characteristic curve (AUC) of the model were calculated by using the test dataset. RESULTS: In the test dataset, the model for detecting CAD achieved an AUC of 0.75 (95% CI, 0.73 to 0.78) with an accuracy of 70.0%. Using the optimal cut-off point, the CAD detection model had sensitivity of 68.7%, specificity of 70.9%, positive predictive value (PPV) of 61.2%, and negative predictive value (NPV) of 77.2%. Our study demonstrates that a well-trained CNN model based solely on ECG could be considered an efficient, low-cost, and noninvasive method of assisting in CAD detection.

An artificial intelligence-based platform for automatically estimating time-averaged wall shear stress in the ascending aorta.

Aims: Aortopathies are a series of disorders requiring multiple indicators to assess risk. Time-averaged wall shear stress (TAWSS) is currently considered as the primary indicator of aortopathies progression, which can only be calculated by Computational Fluid Dynamics (CFD). However, CFD's complexity and high computational cost, greatly limit its application. The study aimed to construct a deep learning platform which could accurately estimate TAWSS in ascending aorta. Methods and results: A total of 154 patients who had thoracic computed tomography angiography were included and randomly divided into two parts: training set (90%, n = 139) and testing set (10%, n = 15). TAWSS were calculated via CFD. The artificial intelligence (AI)-based model was trained and assessed using the dice coefficient (DC), normalized mean absolute error (NMAE), and root mean square error (RMSE). Our AI platform brought into correspondence with the manual segmentation (DC = 0.86) and the CFD findings (NMAE, 7.8773% ± 4.7144%; RMSE, 0.0098 ± 0.0097), while saving 12000-fold computational cost. Conclusion: The high-efficiency and robust AI platform can automatically estimate value and distribution of TAWSS in ascending aorta, which may be suitable for clinical applications and provide potential ideas for CFD-based problem solving.

The glial-specific hypermethylated 3' untranslated region of histone deacetylase 1 may modulates several signal pathways in Alzheimer's disease.

AIMS: Epigenetic regulation plays an important role in the progression of Alzheimer's disease (AD). Here, we identified differential methylation probes (DMP) and investigated their potential mechanistic roles in AD. MAIN METHODS: DMPs were identified via bioinformatic analysis of GSE66351, which was made up with 106 AD samples and 84 control samples derived from three separate brain regions. Differentially expressed genes (DEGs) were analyzed based on GSE5281 comprising 45 control samples and 58 AD samples. Gene ontology (GO), gene set enrichment analysis (GSEA), and protein-protein interaction (PPI) were used to identify pathways and hub genes. KEY FINDINGS: We found 9007 DMPs in Occipital Cortex glia, 1527 in OC neurons, 100 in Temporal Cortex, and 194 in Frontal Cortex. 74 DEGs were identified in Primary Visual Cortex, 67 of which were downregulated while seven upregulated. 482 were upregulated and 697 downregulated in medial temporal gyrus. In superior frontal gyrus, 687 were upregulated and 85 downregulated. GO and PPI revealed that pathways involving epithelial-cell differentiation, cellular responses to lipids, transcription corepressor activities, apoptotic and organ growth were modulated by histone deacetylase 1 (HDAC1) and associated with AD. Additionally, GSEA illustrated that the transforming growth factor beta signaling pathway was significantly enriched in some brain regions and HDAC1 played an important role in this pathway. SIGNIFICANCE: We found the glial-specific 3'UTR of HDAC1 was hypermethylated and HDAC1 was overexpressed in AD patients. Moreover, we also speculate that HDAC1 triggered signaling pathways linked to many different biological processes and functions via the regulation of histone deacetylation.

Bioinformatic gene analysis for potential biomarkers and therapeutic targets of atrial fibrillation-related stroke.

BACKGROUND: Atrial fibrillation (AF) is one of the most prevalent sustained arrhythmias, however, epidemiological data may understate its actual prevalence. Meanwhile, AF is considered to be a major cause of ischemic strokes due to irregular heart-rhythm, coexisting chronic vascular inflammation, and renal insufficiency, and blood stasis. We studied co-expressed genes to understand relationships between atrial fibrillation (AF) and stroke and reveal potential biomarkers and therapeutic targets of AF-related stroke. METHODS: AF-and stroke-related differentially expressed genes (DEGs) were identified via bioinformatic analysis Gene Expression Omnibus (GEO) datasets GSE79768 and GSE58294, respectively. Subsequently, extensive target prediction and network analyses methods were used to assess protein-protein interaction (PPI) networks, Gene Ontology (GO) terms and pathway enrichment for DEGs, and co-expressed DEGs coupled with corresponding predicted miRNAs involved in AF and stroke were assessed as well. RESULTS: We identified 489, 265, 518, and 592 DEGs in left atrial specimens and cardioembolic stroke blood samples at < 3, 5, and 24 h, respectively. LRRK2, CALM1, CXCR4, TLR4, CTNNB1, and CXCR2 may be implicated in AF and the hub-genes of CD19, FGF9, SOX9, GNGT1, and NOG may be associated with stroke. Finally, co-expressed DEGs of ZNF566, PDZK1IP1, ZFHX3, and PITX2 coupled with corresponding predicted miRNAs, especially miR-27a-3p, miR-27b-3p, and miR-494-3p may be significantly associated with AF-related stroke. CONCLUSION: AF and stroke are related and ZNF566, PDZK1IP1, ZFHX3, and PITX2 genes are significantly associated with novel biomarkers involved in AF-related stroke.

Analysis of Genes Involved in Persistent Atrial Fibrillation: Comparisons of 'Trigger' and 'Substrate' Differences.

BACKGROUND/AIMS: Recent research has improved our understanding of the pulmonary vein and surrounding left atrial (LA-PV) junction and the left atrial appendage (LAA), which are considered the 'trigger' and 'substrate' in the development of atrial fibrillation (AF), respectively. Herein, with the aim of identifying the underlying potential genetic mechanisms, we compared differences in gene expression between LA-PV junction and LAA specimens via bioinformatic analysis. METHODS: Microarray data of AF (GSE41177) were downloaded from the Gene Expression Omnibus database. In addition, linear models for microarray data limma powers differential expression analyses and weighted correlation network analysis (WGCNA) were applied. RESULTS: From the differential expression analyses, 152 differentially expressed genes and hub genes, including LEP, FOS, EDN1, NMU, CALB2, TAC1, and PPBP, were identified. Our analysis revealed that the maps of extracellular matrix (ECM)-receptor interactions, PI3K-Akt and Wnt signaling pathways, and ventricular cardiac muscle tissue morphogenesis were significantly enriched. In addition, the WGCNA results showed high correlations between genes and related genetic clusters to external clinical characteristics. Maps of the ECM-receptor interactions, chemokine signaling pathways, and the cell cycle were significantly enriched in the genes of corresponding modules and closely associated with AF duration, left atrial diameter, and left ventricular ejection function, respectively. Similarly, mapping of the TNF signaling pathway indicated significant association with genetic traits of ischemic heart disease, hypertension, and diabetes comorbidity. CONCLUSIONS: The ECM-receptor interaction as a possible central node of comparison between LA-PV and LAA samples reflected the special functional roles of 'triggers' and 'substrates' and may be closely associated with AF duration. Furthermore, LEP, FOS, EDN1, NMU, CALB2, TAC1, and PPBP genes may be implicated in the occurrence and maintenance of AF through their interactions with each other.

Efficacy of Statin Therapy Related to Baseline Renal Function in Patients with Rheumatic Heart Disease Undergoing Cardiac Surgery.

BACKGROUND: Renal impairment increases the risk of cardiovascular events and perioperative complications in patients with heart valve disease. This study aimed to determine the perioperative benefit of statin treatment related to baseline renal function in patients with rheumatic heart disease (RHD) who had cardiac surgery. METHODS AND RESULTS: We performed a retrospective study on 136 patients with RHD who underwent valve replacement surgery. The mean age of the patients was 56.2 years, 59.6% were female, 8.8% patients had diabetes mellitus, and 27.2% of patients had hypertension. Overall, 3 patients died, 2 underwent reoperation, and 25 underwent thoracentesis during the study period. For patients with renal impairment, there was a higher risk of thoracic puncture (odds ratio [OR]: 3.33; 95% confidence interval [CI]: 1.36, 8.11; P < 0.01) and a longer time of drainage (difference in means: 1; 95% CI: 0.88, 1.12; P < 0.01), intensive care unit (ICU) stay (difference in means: 0.2; 95% CI: 0.17, 0.23; P = 0.02), and hospital stay (difference in means: 6.6; 95% CI: 6.15, 7.05; P < 0.01) compared with normal renal function. Furthermore, statins were associated with a reduction in drainage time (difference in means: -1.50; 95% CI: -1.86, -1.14; P = 0.02), ICU stay (difference in means: -0.30; 95% CI: -0.40, -0.20; P = 0.05), and hospital stay (difference in means: -5.40; 95% CI: -6.57, -4.23; P < 0.01) in patients with renal impairment (interaction, P ≤ 0.05 for all), but not in those with normal renal function. CONCLUSION: Statins have a greater clinical benefit in perioperative cardiac surgery with renal impairment. Statins are associated with a comparatively lower risk of thoracic puncture, as well as a reduced trend toward a reduction in drainage time, ICU stay, and hospital stay.

Biatrial versus Isolated Left Atrial Ablation in Atrial Fibrillation: A Systematic Review and Meta-Analysis.

OBJECTIVE: The outcomes of biatrial ablation (BA) and isolated left atrial ablation (LA) in atrial fibrillation remain inconclusive. In this meta-analysis, we assess the currently available evidence to compare outcomes between BA and LA. METHODS: Electronic searches were performed from database inception to December 2016, and relevant studies were accessed. Odds ratios and weight mean differences with 95% confidence intervals are reported. Twenty-one studies comprising 3609 patients were included in the present meta-analysis. RESULTS: The prevalence of sinus rhythm in the BA cohort was similar to that in the LA cohort at discharge, at 12 months, and after more than 1 year of follow-up. However, at 6 months, the prevalence of sinus rhythm was higher in the BA cohort than in the LA cohort. The rate of permanent pacemaker implantation was higher in the BA cohort than in the LA cohort. However, 30-day and late mortality and neurological events were similar between the BA and LA groups. CONCLUSION: There was no significant difference in the rate of restored sinus rhythm, the risk of death, and cerebrovascular events between BA and LA, but BA had a higher rate of permanent pacemaker implantation.

Safety and efficacy of the perioperative administration of recombinant human brain natriuretic peptide (rhBNP): a systematic review and meta-analysis.

OBJECTIVE: Retrospective studies and a meta-analysis were performed to evaluate the safety and effectiveness of the perioperative administration of recombinant human brain natriuretic peptide (rhBNP) during cardiac surgery under extracorporeal circulation. METHODS: Computerized literature searches were performed in Medline, Embase, The Cochrane Library, CNKI, CBM, and WANFANG to find randomized controlled trials (RCTs) related to the perioperative administration of rhBNP during cardiac surgery starting from the database inception until December 2016. Two researchers independently performed study screening, information extraction, and quality evaluation according to the inclusion/exclusion criteria, and a meta-analysis was performed using RevMan 5.2 software. RESULTS: A total of 12 studies were analyzed, including 12 RCTs and 727 patients. The meta-analysis results indicated that the perioperative administration of rhBNP could reduce the occurrence rate of postoperative complications, length of intensive care unit (ICU) stay, length of hospital stay, and serum creatinine (Scr) levels, and increase the 24-hour urine volume; however, it did not affect the postoperative mortality rate. CONCLUSION: The perioperative administration of rhBNP during cardiac surgery was safe and effective, and could improve the prognosis of the patients.

SIRT5 and post-translational protein modifications: A potential therapeutic target for myocardial ischemia-reperfusion injury with regard to mitochondrial dynamics and oxidative metabolism.

SIRT5 is a sirtuin family member that participates in dynamic and reversible protein chemical modification after translation. It has pivotal roles in the regulation of numerous aspects of myocardial energy metabolism and cardiac functions. Recent studies suggest that down-regulation of this regulator significantly increased the extent of myocardial infarction during ischemia-reperfusion injury (IRI). Accordingly, SIRT5 is emerging as a major contributor to the pathogenesis of IRI and may possess therapeutic potential for reversing mitochondrial respiratory chain disturbances and cellular damage attributed to ischemia-reperfusion. To better understand this specific mechanism, we reviewed the structure of SIRT5, its gene distribution and the SIRT5 pathways that influence myocardial IRI associated with mitochondrial dynamics and oxidative phosphorylation.

Efficacy and Mechanism of Preoperative Simvastatin Therapy on Myocardial Protection after Extracorporeal Circulation.

BACKGROUND: Cardiopulmonary bypass (CPB) causes systemic inflammatory response and ischemia-reperfusion (IR) injury. OBJECTIVE: To investigate the effect and mechanism of simvastatin on myocardial injury in cardiac valve surgery with CPB. METHODS: One hundred thirty patients were randomly assigned to the statin group (n = 65) or control group (n = 65). Simvastatin was administered preoperatively and postoperatively. Duration of intensive care unit stay, duration of assisted ventilation, and left ventricular ejection fraction were recorded. Plasma was analysed for troponin T (cTnT), isoenzyme of creatine kinase (CK-MB), tumor necrosis factor alpha (TNF-α), interleukin-6 (IL-6), and interleukin-8 (IL-8). Ultrastructure of the myocardium and autophagosomes were observed. Beclin-1, LC3-II/I, P62, AMPK, and the phosphorylation of AMPK in cardiomyocytes were detected. RESULTS: Simvastatin significantly reduced the duration of assisted ventilation (P = 0.030) and ejection fraction was significantly higher in the statin group (P = 0.024). Simvastatin significantly reduced the levels of cTnT, CK-MB, TNF-α, IL-6, and IL-8 (P < 0.05), reduced the expression of LC3-II/LC3-I and Beclin 1, and increased the expression of phosphorylation of AMPK. Simvastatin reduced the generation of autophagosomes and the ultrastructural injuries to myocardium. CONCLUSION: Perioperative statin therapy reduced myocardial injury by regulating myocardial autophagy and activating the phosphorylation of AMPK. The registration number of this study is ChiCTR-TRC-14005164.

Meta-analysis of safety and efficacy for direct oral anticoagulation treatment of non-valvular atrial fibrillation in relation to renal function.

INTRODUCTION: We performed a meta-analysis of the safety and efficacy of anticoagulation treatment for atrial fibrillation (AF) in relation to renal function. We also examined the change in estimated glomerular filtration rate (eGFR) from baseline and compared the outcomes for patients with stable and worsening renal function. MATERIALS AND METHODS: We selected studies that used randomized controlled trials in which outcomes for direct oral anticoagulants (DOACs) (dabigatran, rivaroxaban, apixaban, or edoxaban) were compared with those for warfarin in AF patients with normal, mild or moderate renal function, except the severe one (creatinine clearance<30). RESULTS: We assessed five clinical trials, involving 72,608 patients. Pooled analysis indicated that the risk of stroke was lower for DOACs than for warfarin among patients with mild renal impairment (Risk ratio, 0.79; 95% confidence interval, 0.68-0.91) and moderate renal impairment (0.80, 0.69-0.92). No major differences were found in patients with normal renal function. Additionally, DOACs were associated with fewer major bleeds among patients with normal (0.77, 0.70-0.84), mild (0.86, 0.77-0.95), and moderate renal impairment (0.73, 0.65-0.82). Among those treated with DOACs, a lower dosage was associated with lower risk of major bleeding (0.75, 0.68-0.83) and higher risk of stroke or systemic embolism (1.28, 1.12-1.47). Further, DOACs tended to be associated with a lower estimated glomerular filtration rate (eGFR) than warfarin even after 30months. Finally, we found significant differences in the risk of stroke (2.09, 1.64-2.68) and major bleeding (2.01, 1.66-2.42) between patients with stable and worsening renal function. CONCLUSIONS: DOACs have a greater clinical benefit than warfarin with respect to renal function. They are associated with a comparatively lower risk of stroke and major bleeding, as well lower eGFR. This suggests these agents are a better choice in patients with renal disease.

Neurocardiology: Cardiovascular Changes and Specific Brain Region Infarcts.

There are complex and dynamic reflex control networks between the heart and the brain, including cardiac and intrathoracic ganglia, spinal cord, brainstem, and central nucleus. Recent literature based on animal model and clinical trials indicates a close link between cardiac function and nervous systems. It is noteworthy that the autonomic nervous-based therapeutics has shown great potential in the management of atrial fibrillation, ventricular arrhythmia, and myocardial remodeling. However, the potential mechanisms of postoperative brain injury and cardiovascular changes, particularly heart rate variability and the presence of arrhythmias, are not understood. In this chapter, we will describe mechanisms of brain damage undergoing cardiac surgery and focus on the interaction between cardiovascular changes and damage to specific brain regions.

Application and Progress of Combined Mesenchymal Stem Cell Transplantation in the Treatment of Ischemic Cardiomyopathy.

Treatment of ischemic cardiomyopathy caused by myocardial infarction (MI) using mesenchymal stem cell (MSC) transplantation is a widely researched field, with promising clinical application. However, the low survival rate of transplanted cells has a severe impact on treatment outcome. Currently, research is focused on investigating the strategy of combining genetic engineering, tissue engineering materials, and drug/hypoxia preconditioning to improve ischemic cardiomyopathy treatment outcome using MSC transplantation treatment (MSCTT). This review discusses the application and progress of these techniques.

Influence of caspase-3 silencing on the proliferation and apoptosis of rat bone marrow mesenchymal stem cells under hypoxia.

AIMS: To investigate the effects of caspase-3 silencing on the proliferation and apoptosis of rat bone marrow mesenchymal stem cells (MSCs) under hypoxia. METHODS: Rat bone marrow MSCs were transfected with a recombinant shRNA lentivirus targeting caspase-3 expression. Protein expression of caspase-3 was measured by western blotting. Cell proliferation was measured with MTS, and the cell cycle was analyzed by flow cytometry. The apoptosis rate was measured at various time points under hypoxia. Apoptotic morphology was assessed by Hoechst 33258 staining. mRNA levels of caspase-3, Bcl-2, and Bax were measured by real-time PCR. RESULTS: Western blotting showed that the rat MSCs were stably transfected with the shRNA targeting caspase-3 by a significant reduction of caspase-3 expression. Silencing of caspase-3 expression resulted in a significant increase of MSC proliferation (P < 0.05), an increase of cells in S-phase (52.66 ± 0.30%), and a significant decrease of apoptotic MSCs (P < 0.05). These effects exhibited a slow increase during hypoxic culture. Furthermore, caspase-3 silencing significantly down-regulated mRNA expression of caspase-3 (P < 0.01) and Bax (P < 0.01), and up-regulated Bcl-2 mRNA expression (p < 0.01), thereby increasing the ratio of Bcl-2/Bax (P < 0.05). CONCLUSION: Caspase-3 silencing modulates the cell cycle of MSCs, promotes cell proliferation, and enhances the anti-apoptotic capacity of MSCs under hypoxia in vitro.

A significant risk factor for poststroke depression: the depression-related subnetwork.

BACKGROUND: Despite being one of the direct causes of depression, whether stroke-induced neuroanatomical deterioration actually plays an important role in the onset of poststroke depression (PSD) is controversial. We assessed the structural basis of PSD, particularly with regard to white matter connectivity. METHODS: We evaluated lesion index, fractional anisotropy (FA) reduction and brain structural networks and then analyzed whole brain voxel-based lesions and FA maps. To understand brain damage in the context of brain connectivity, we used a graph theoretical approach. We selected nodes whose degree correlated with the Hamilton Rating Scale for Depression score (p < 0.05, false discovery rate-corrected), after controlling for age, sex, years of education, lesion size, Mini Mental State Examination score and National Institutes of Health Stroke Scale score. We used Poisson regression with robust standard errors to assess the contribution of the identified network toward poststroke major depression. RESULTS: We included 116 stroke patients in the study. Fourteen patients (12.1%) had diagnoses of major depression and 26 (22.4%) had mild depression. We found that lesions in the right insular cortex, left putamen and right superior longitudinal fasciculus as well as FA reductions in broader areas were all associated with major depression. Seventeen nodes were selected to build the depression-related subnetwork. Decreased local efficiency of the subnetwork was a significant risk factor for poststroke major depression (relative risk 0.84, 95% confidence interval 0.72-0.98, p = 0.027). LIMITATIONS: The inability of DTI tractography to process fibre crossings may have resulted in inaccurate construction of white matter networks and affected statistical findings. CONCLUSION: The present study provides, to our knowledge, the first graph theoretical analysis of white matter networks linked to poststroke major depression. These findings provide new insights into the neuroanatomical substrates of depression that develops after stroke.

Erysipelothrix rhusiopathiae-induced aortic valve endocarditis: case report and literature review.

Erysipelothrix rhusiopathiae is a pathogen of zoonosis often associated with occupational exposure. Although Erysipelothrix rhusiopathiae infection has high mortality, the heart valves in humans are rarely involved. The clinical data of a case of a 65-year-old male with Erysipelothrix rhusiopathiae-induced aortic valve endocarditis was summarized retrospectively and analyzed with a literature review. Based on a literature review and our experience, cases of E. rhusiopathiae-induced aortic valve endocarditis are extremely rare and surgical treatment for this condition is useful and recommended.

Voxel-based analysis of fractional anisotropy in post-stroke apathy.

OBJECTIVE: To explore the structural basis of post-stroke apathy by using voxel-based analysis (VBA) of fractional anisotropy (FA) maps. METHODS: We enrolled 54 consecutive patients with ischemic stroke during convalescence, and divided them into apathy (n = 31) and non-apathy (n = 23) groups. We obtained magnetic resonance images of their brains, including T1, T2 and DTI sequences. Age, sex, education level, Hamilton Depression Scale (HAMD) scores, Mini-Mental State Examination (MMSE) scores, National Institutes of Health Stroke Scale (NIHSS) scores, and infarct locations for the two groups were compared. Finally, to investigate the structural basis of post-stroke apathy, VBA of FA maps was performed in which we included the variables that a univariate analysis determined had P-values less than 0.20 as covariates. RESULTS: HAMD (P = 0.01) and MMSE (P<0.01) scores differed significantly between the apathy and non-apathy groups. After controlling for age, education level, HAMD scores, and MMSE scores, significant FA reduction was detected in four clusters with peak voxels at the genu of the corpus callosum (X = -16, Y = 30, Z = 8), left anterior corona radiata (-22, 30, 10), splenium of the corpus callosum (-24, -56, 18), and right inferior frontal gyrus white matter (52, 24, 18), after family-wise error correction for multiple comparisons. CONCLUSIONS: Post-stroke apathy is related to depression and cognitive decline. Damage to the genu of the corpus callosum, left anterior corona radiata, splenium of the corpus callosum, and white matter in the right inferior frontal gyrus may lead to apathy after ischemic stroke.